To make sense of complex data in inquiry, students must develop reflective modes of ...... The two classes each are in her room for half the school day (alternating ...... represent earth's crust (âlike when we did the orange peelâ), and to the nature of .... other African-American girls, Charlisse, is also a member of our focus table ...
NORTHWESTERN UNIVERSITY
Making sense of complex data: A framework for studying students’ development of reflective inquiry dispositions
A DISSERTATION SUBMITTED TO THE GRADUATE SCHOOL IN PARTIAL FULFILMENT OF THE REQUIREMENTS for the degree of DOCTOR OF PHILOSOPHY Field of EDUCATION AND SOCIAL POLICY – LEARNING SCIENCES
By Joshua Radinsky EVANSTON, ILLINOIS JUNE 2000
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Abstract TITLE: Making sense of complex data: A conceptual framework for studying students’ development of reflective inquiry dispositions To make sense of complex data in inquiry, students must develop reflective modes of classroom work. This study examines the process of developing such reflective dispositions for individual students, in the context of a middle-school earth science inquiry unit designed by the researchers and collaborating teachers. Valid characterization of this learning process requires a conceptual framework through which to attend to the multiple variables that contribute to dispositional learning. The proposed conceptual framework identifies a reflective disposition as a property not just of the individual, but of the individual within an activity system. Relevant variables for study include elements of the classroom activity system, elements of the intended domain of reflective data analysis, and elements of the individual student’s modes of understanding. These are proposed as three contexts of reflection, referred to as the “task context,” the “data context,” and the “role context.” This three-context framework for understanding reflection in inquiry is used as a tool for data analysis, characterizing the dispositional learning of each focus student in the study. Reflection was found to be an often-shared social process, shaping and being shaped by the negotiation of the meaning of activity. Learning was mediated by interactions between group interactional modes (in the task context) and individuals’ roles (in the role context). Two focus groups studied were found to have markedly different modes of interaction: one characterized as a “comfort zone” for work with complex data, the other a “confrontation zone.” These modes afforded the development of different roles, or modes of participation, for each student. Learning to make sense of complex data was situated within the development of these new roles. The framework and data analysis suggest a coherent approach to representing social activity patterns, individual development, and content-area instructional goals within a common conceptual framework. This is a valuable contribution in that it locates other bodies of educational research in relation to one another.
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Acknowledgements My wife Julie has been my constant partner and inspiration as I’ve been learning to do classroom research, making curriculum materials, and writing this dissertation. Our boys Benjy and Sammy keep us learning about learning in life’s many adventures. Jules, thanks for putting me through school, in so many ways – on to our next project! Ben Loh and Jennifer Mundt Leimberer are partners in all the work discussed in this dissertation, and much more. Jen and Ben, you two are the best collaborators, teachers, designers, and fellow-learners I could imagine working with. Thanks for your patience, high standards, shared insights, and dedication to students. You are both great role models for pursuing excellence while nailing the messy details! I have learned a ton from both of you, and I hope to keep on doing so in our future collaborations. Sue Marshall, thank you for your partnership, creative brainstorming, and ongoing analysis during the Earth Structures unit; and special thanks for pulling me through difficult times during winter 1998-99 when Sammy was in the hospital. Jean Bramlette, Sonia Flores, Jennifer Mundt Leimberer, Jeni Olson, and Thea Raedeke, thanks for the collaborative learning we have done together around this unit. Thanks especially for sharing your classrooms and your curriculum planning process, and for being willing to work with rough materials and ideas in order to make them better. Louis Gomez, Brian Reiser, and Danny Edelson, thanks for creating such a supportive and creative intellectual atmosphere in the SIBLE project within which this work could happen. Sincerest thanks to my dissertation committee, Karen Fuson, Louis Gomez, Carol Lee, and Brian Reiser, each of whom has challenged me in a different way to improve this work. Thanks especially to the students at Boone, Inter-American, Hayt, Saucedo, and Haines elementary schools, who have been patient and cooperative collaborators in the curriculum design process, and thoughtful contributors to the ideas presented in this dissertation.
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Table of Contents 1) INTRODUCTION ....................................................................................................... 1 2) CONCEPTUAL FRAMEWORK ............................................................................ 10 2.1) WHAT IS REFLECTION? ........................................................................................ 10 2.2) THREE CONTEXTS FOR REFLECTION ON ACTIVITY WITH DATA ............................. 20 2.3) SUMMARY: A FRAMEWORK FOR STUDYING REFLECTION IN INQUIRY ................. 46 3) DESIGN OF THIS STUDY: RESEARCH METHODS ......................................... 49 3.1) RESEARCH SITES AND PARTICIPANTS: THREE CLASSROOMS STUDIED.................. 49 3.2) LEVEL OF ANALYSIS: FOCUS ON SMALL GROUPS................................................. 52 3.3) DATA COLLECTED................................................................................................ 55 3.4) PROCESS FOR ANALYZING THE DATA ................................................................... 57 4) DESIGN RATIONALE OF THE UNIT................................................................... 60 4.1) PURPOSE OF A DESIGN RATIONALE....................................................................... 60 4.2) BRIEF DESIGN HISTORY OF THE UNIT.................................................................... 62 4.3) WAYS OF THINKING ABOUT GEOLOGICAL DATA................................................... 68 4.4) TWO DESIGN APPROACHES BASED ON A TRAJECTORY OF ARTIFACTS ................... 72 4.5) PEDAGOGICAL GOALS OF FOUR FOCUS ACTIVITIES ............................................. 77 5) DATA ANALYSIS: REFLECTION IN CLASSROOM ENACTMENTS .......... 85 5.1) PROTOTYPICAL EXAMPLES: WHAT DID REFLECTION LOOK LIKE? ........................ 86 5.2) CASE 1: THE “COMFORT ZONE”........................................................................... 97 5.3) CASE 2: THE “CONFRONTATION ZONE”.............................................................. 133 5.4) VALIDITY OF THE CONSTRUCTS: OTHER GROUPS AS REFERENCE POINTS ............ 159 v
6) DISCUSSION............................................................................................................ 167 6.1) WHAT WE’VE LEARNED ABOUT REFLECTIVE INQUIRY ........................................ 167 6.2) DESIGN IMPLICATIONS ........................................................................................ 175 7) CONCLUSIONS AND FUTURE RESEARCH..................................................... 183 REFERENCES.............................................................................................................. 186 APPENDIX A: INTERVIEW PROTOCOLS........................................................... 195 PROTOCOL 1: INDIVIDUAL INTERVIEW. ..................................................................... 196 PROTOCOL 2: GROUP INQUIRY TASK ......................................................................... 204
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List of tables TABLE 1: A DEWEYAN MODEL OF REFLECTION IN INQUIRY. ........................................ 19 TABLE 2: THE EARTH STRUCTURES AND PROCESSES UNIT .......................................... 78 TABLE 3: REPRESENTATION OF ACTIVITY CONTEXTS FOR THE DATA ANALYSIS. .......... 86 TABLE 4: TIMELINE OF UNIT ENACTMENT AT BOONE ................................................... 96 TABLE 5: LATANYA AND DAVID AVOID EXPLAINING DATA . ..................................... 114 TABLE 6: A 5-MINUTE SMALL-GROUP DISCUSSION IN THE “CONFRONTATION ZONE” 146 TABLE 7: EVIDENCE OF TROY AND AARON’S COMFORT ZONE.................................. 161
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1) Introduction
Computers can bring to classrooms increasingly sophisticated tools for representing and organizing large amounts of information. To inform our efforts to design curriculum and instruction with which to take advantage of these tools, we must address a fundamental question: How do students learn to make sense of complex information through classroom inquiry? The answer to a “how” question about learning must involve a description of a process of change for students. Becoming more adept at figuring out big datasets means changing modes of thinking and acting when faced with complexity – from less productive, to more productive. Dewey (1933) defined this change as developing a reflective mode of inquiry: “beginning with practical manipulations” of artifacts used in the classroom, but then “transferring interest to intellectual matters” (p. 224-5). Learning to make sense of complexity involves learning to reflect productively. What does this process of learning to reflectively engage complex data look like? And how can we characterize this learning process in a given domain of inquiry? In this dissertation I propose a conceptual framework for representing and analyzing changes in the nature of students’ reflectiveness in classroom inquiry using complex datasets. The goal of the proposed framework is to identify factors that contribute to the development of more reflective dispositions in inquiry, and to examine how these factors interact to shape what is learned. The need for new conceptual frameworks
Research frameworks afford and also constrain our understanding of learning. One of the great challenges for educational researchers over the last decade has been to develop frameworks that represent learning contexts as more than bilateral interactions between subjects and interventions. Theories of learning must be grounded in an understanding not just of individual cognition, but of systems of activity in which those individuals act. For example, Jean Lave (1990) draws attention to the inadequacy of an “expert/novice” framework for studying science learning in high school classrooms, in light of Eckert’s (1989) culturally-informed framework for representing participation patterns of “jocks” and “burnouts” in high school science classes:
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If … current theories of the learner and conventional interpretations of variations in students’ performance in research settings are irrelevant and erroneous, we might worry about the power of research on learning to broaden our understanding of effective methods of teaching and learning in schools today. (Lave, 1990, p. 255) Lave’s criticism is that knowing and learning are situated – and we know too little about the situation, or how knowledge gets constructed through social interaction in the classroom. If we don’t understand the activity of constructing knowledge in the classroom, our effectiveness at designing good interventions will suffer. Conceptual frameworks for research on learning often assume linear relationships – such as when we study the impact of a certain curriculum design (or instructional strategy) on changes in student understanding. Such frameworks often ignore so many salient aspects of the activity context that they shed little light on how learning happens. On the other hand, very abstract frameworks – such as metaphors for teaching-learning processes – can provide valuable insights, but often do not enable us to represent the effects of particular elements within a learning environment. I propose that inquiry learning can be represented as interactions among factors in classroom activity systems. This type of factor-relationship representation can be thought of as a kind of modeling. Social and intellectual relationships in classrooms are not simple enough to model quantitatively, as we might model global warming or other ecosystemic processes, but the value of a model lies not only in predictive or computational functions. Models also are valuable as symbol systems for identifying relevant factors in a complex system, and for characterizing relationships and processes involving these factors. The framework developed here is intended as such a model for characterizing changing reflective inquiry dispositions, and with it I attempt to represent relationships among elements which are usually considered in isolation from one another. Representing inquiry dispositions
Students’ dispositions in scientific inquiry are often characterized as properties of the individual, such as an internal psychological state or ability, or a set of characteristics, beliefs, or understandings. These characterizations do not account for the interdependent nature of modes of thinking and activity contexts. Rather than defining reflectiveness as a local property of the individual, I suggest that reflective thinking is an emergent property of an individual’s interaction with an activity system. To understand it, I
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suggest that we need to represent both characteristics of the individual, and characteristics of the activity system in which the individual participates. Furthermore, the kinds of reflective thinking that we, as educators, want to instill in students are not usually generic or universal, pertaining similarly to all subject areas. Rather, they are dependent upon the domain of inquiry, or the family of conceptual connections that are the goals of curricular and instructional design. Therefore, to study the development of reflective thinking, our framework must represent not only the individual and the activity context, but also the mode of reflective thinking which a teacher and/or a curriculum designer intends students to develop. So to study the process of students learning to think more reflectively in inquiry, I suggest that there are three arenas that we must examine within a common framework: •
an intended mode of reflective domain thinking;
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a system of activity within which we hope this mode will develop; and
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individual factors which contribute to a student’s mode of participation in inquiry.
Each of these constitutes a context for the development of reflective dispositions. This dissertation attempts to articulate these three contexts and their interrelations, to develop a framework with which to characterize changes in inquiry dispositions. Prior research has shed much light on each of these three contexts separately, as they relate to reflective inquiry with complex datasets. Literature on scientists’ thinking (e.g. Reif and Larkin 1991; Dunbar 1995), metacognitive strategies (e.g. Schoenfeld 1987; Kuhn 1993), and various domain analyses for designing curriculum (e.g. Tabak, Smith et al. 1996; Smith and Reiser 1998; Radinsky, Loh et al. 1999) provide valuable representations of particular understandings, inquiry skills, strategies, and habits of mind which we might want students to learn (context #1 above). Analyses of lesson structures (e.g. Johnson and Johnson 1982; Kagan 1992), socio-cultural activity systems (e.g. (Rogoff 1995; Polman 1997), and classroom discourse (e.g. Gutierrez 1993; Lin 1993) provide important models for representing the complexities of everyday classroom interactions (context #2). And literature on identity and culture (e.g. Eckert 1989; New London Group 1996), student motivation (e.g. Malone 1981; Dweck 1986), and student conceptions of science (e.g. Carey 1988; Sandoval and Reiser 1997) provide valuable insights into the worlds and minds of students (context #3). The framework developed in this dissertation attempts to locate these three contexts of classroom learning in relation to one another. This effort is important in that each
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research focus (on domain thinking, on classroom activity, and on student understandings) must define itself in relation to the others, in order to avoid some misleading assumptions. For example, curriculum does not act independently upon students to effect given learning outcomes. Students’ dispositions and beliefs about curricular domains do not exist independently of classroom experiences. And the events of a day in the classroom cannot be well interpreted without considering both the instructional context, and participants’ identities. Recognizing the fallacy of these analytical pitfalls is not enough. As teachers and researchers, we need analytical frameworks that will keep us mindful of the interacting contexts that shape learning experiences. Individual teachers and students, the curriculum, and classroom activity exist in a tight relationship with one another. For these reasons, I propose an analytical framework representing interactions among the three. Questions addressed in this study
In this study I address the question: How do students learn to make sense of complex information through classroom inquiry? The question is not simply how they do make sense of complex data, but rather how their ways of making sense of such data change over time, leading to different domain understandings. In particular, the study asks: How do students develop more reflective inquiry dispositions? And how do elements of classroom activity systems interact to promote and constrain this dispositional learning? The interaction that is foregrounded in this study is the relationship between students’ small-group interaction patterns, and individual students’ modes of participation in inquiry activity. This interaction was found to mediate the development of reflective thinking in the domain. Other important factors affecting the development of reflective inquiry habits, including teachers’ instructional strategies and curriculum designs, are backgrounded in the analysis. This is not to say that they are not important, but rather that their effects can be interpreted through the lens of student, and small group, participation patterns. Analysis of the same data, foregrounding teacher-student or student-artifact interactions, would greatly expand on the findings of this study. I choose to focus on student participation patterns (individual and group) as mediators of learning for two reasons. First, teacher and curriculum “effects” on student learning are the most common focus of educational research – this means that we often “hear” mainly what the teacher says, and “see” mainly the curriculum materials. As a result, we, as a community, may tacitly assume that instructional strategies and curriculum designs are
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the only mediators of learning. On the other hand, we have less awareness of how students construct understandings through discourse, and how the interactional patterns of students mediate what is learned. The second reason for foregrounding student interaction patterns and modes of participation lies in the concept of dispositional learning. By focusing on how students develop a reflective disposition in work with complex data, we require a detailed picture of how students act. Whereas the accumulation of factual and procedural knowledge might be identified in interviews or tests, dispositional learning is observable only in changes in participation patterns. This means that we must have a foreground focus on how students act in day-to-day activities with data – most of which take place in small groups, and often not in direct interaction with the teacher. The research questions are addressed on two levels: first through the development of a conceptual framework which can be used to characterize learning to reflect in inquiry with complex data; and second through detailed case studies of five middle-school students’ learning processes over the course of the enactment of an inquiry science unit. The conceptual framework proposed here has emerged through the present study and data analysis. It is informed by the literature reviewed below in Section 2, by the emergent analysis of classroom discourse, and by reflective conversations with collaborating teachers and researchers participating in the study. Though the analytical framework is presented here first, in Section 2, and the case studies of student learning follow later in Section 5, the two actually were developed in parallel. Each informs the other, and both the framework and the case studies are presented here as products of this research. Context of this research
This study is part of a larger program of design research, seeking to improve the educational community’s understanding of how students learn through inquiry with complex data. Why complex data?
As members of this society, we have increasing access to large amounts of information. New information media shape the activity of sociologists and police officers, moviegoers and grocery shoppers, sports fans and geophysicists. While different sectors of society are affected in very different ways by these changes in media of information, few are unaffected. Being able to figure things out from complex data is an increasingly important skill in our society. It can empower us in many different realms of life –
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professional, political, intellectual, artistic, even physical and spiritual. Being unable to make sense of complex data clearly leaves us at a disadvantage, more subject to persuasion in all its new high-tech forms. For the most part, the world of classroom activity has remained insulated from these changes going on in other sectors of our lives. According to a recent article in the New York Times (9/29/99), although access to computers and the Internet has increased in schools nationwide, “many teachers remain befuddled about how exactly to incorporate the machines into their lesson plans.” The development of software, curriculum, and schools’ computer infrastructure often proceed independently of one another, leaving teachers with great difficulty integrating new media into their practice. This is especially true in urban public schools, where tele-computing technologies usually remain peripheral to most activity (Piller 1992; Benton Foundation 1998). The result of this is that many students, especially in urban areas, do not have experiences in school in which they learn to use technological tools to make sense of complex information. This is a missed opportunity: for many students, school could well be the only place where they might have access to many informational technologies. As educators in an information-rich society, we have a responsibility to provide students with these experiences in the classroom. But incorporating complex datasets into classroom inquiry presents many challenges for students and teachers. Students tend to have trouble managing the large amounts of information they encounter in these environments (Audet and Abegg 1996), and managing the work of classroom investigations in general (Schauble, Glaser et al. 1995). When allowed to openly explore in data-rich environments, students tend to look through datasets in a haphazard and non-reflective manner, which significantly limits learning opportunities with these tools (deJong and vanJoolingen 1998). The mode of work involved in making sense of complex datasets is often unfamiliar and disorienting for students. What is actually learned by students as they attempt to make meaning of confusing data is very difficult to predict, with a great potential for developing misleading conceptions through using reasoning strategies that are inappropriate to the situation (Chinn and Brewer 1993). Conducting classroom inquiry using complex datasets is difficult for teachers for a number of other reasons as well. New academic standards in science education demand that teachers help students learn to use these types of computer tools productively (CPS 1997; NRC 1998). But teachers face many logistical problems in facilitating a roomful of
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students trying to make sense of a flood of information. The time required for incorporating tele-computing tools into classroom work can conflict with teachers meeting the demands of accountability to content standards and curriculum frameworks (J. Mundt, personal communication, 1998). Working with complex data in the classroom requires teachers to achieve a level of familiarity with the domain and the data materials themselves that can be extremely demanding. The SIBLE Project: Designing to promote reflection in inquiry
The present study is part of an effort to develop mutually-informing models of classroom activity and design approaches for using complex computer-based datasets in classroom inquiry. The Supportive Inquiry Based Learning Environments (SIBLE) Project has pursued this program of “classroom-centered design” for the last five years (Loh, Radinsky et al. 1997; Radinsky, Loh et al. 1999; Loh, Reiser et al. in press). Our work has centered on the design and use of the Progress Portfolio, a software environment for classroom inquiry projects, as well as various inquiry curricula that use complex datasets. This work is a collaboration with middle- and high-school teachers, priumarily in Chicago Public Schools. The SIBLE work has examined several aspects of reflection in classroom inquiry. Our design research with the Progress Portfolio software has studied reflection by making the processes and products of classroom inquiry into manipulable objects for students within a computer workspace (Loh, Reiser et al. in press). Other studies have examined the instructional opportunities that are created in teacher-student discourse around such objects over the course of an investigation, as the teacher prompts students to reflect (Loh, Radinsky et al. 1998). In tandem with this software-design research, the SIBLE project has also studied design dimensions of inquiry curriculum (Radinsky, Loh et al. 1998; Radinsky, Loh et al. 1999). This line of research has focused on particular design strategies for promoting reflection in inquiry with complex data. These studies examine the design of materials and lesson structures intended to promote reflection, both with and without the Progress Portfolio. Current work of the SIBLE Project has expanded to focus on students’ development of communication skills around scientific inquiry projects (Loh and Alamar 2000); the role of computer-based artifacts in supporting communication and reflection about inquiry (Marshall 2000); and student and teacher beliefs about the Progress Portfolio as an inquiry support tool (Matese 2000).
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Curriculum design context: The Earth Structures and Processes unit
The present study focuses on enactments of a middle-school curriculum unit designed by SIBLE researchers and teachers, called “Earth Structures and Processes: Exploring earth’s crust using models and data” (Radinsky, Loh et al. 1999). Participating teachers and I collaborated both in the design of the unit, and in developing instructional approaches during enactments. My role in the classrooms was that of a participant observer, assisting teachers in conducting the unit. The purpose of this study is to use a designer’s inside perspective on the lessons to provide insights into student activity and learning. Earth Structures and Processes is a 10-week inquiry unit on plate tectonics and geological change, utilizing a variety of datasets on paper, in data visualization software, and on the Internet. The enactments took place in 6th and 7th grade classrooms in three Chicago Public Schools. The Earth Structures and Processes unit embodies design approaches that seem to have great promise for helping teachers develop classroom experiences in which students learn to make sense of complex data. Though these design approaches are not the focus of this study per se, my hope is that the analysis of dispositional learning around work with complex data can serve as a strong foundation for developing design principles for both curriculum materials and instructional strategies. The successes that we have experienced with this curriculum with students in urban public school settings provides reasonable optimism for further developing this design work in other curricular domains. Overview of the dissertation
The dissertation is organized in six sections following this introduction (Section 1). Section 2 describes the analytical framework developed in the study. It overviews the body of research on which this study builds. The literature review is organized in the form of an argument for the development of the conceptual framework which is used in the subsequent data analysis. While the proposed framework does draw on prior research, it is also informed by the data analysis itself, and as such is a product of the study rather than a pre-existing assumption underlying the research design. Section 3 describes the research methods for designing and conducting the study and analyzing the collected data. The emergent nature of the analytical framework is discussed here, in addition to the details of data collection and analysis.
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Section 4 is an overview of the curriculum unit which is the basis of this study. The design rationale of the unit is provided in order to contextualize for the reader the student discussions examined later in the data analysis. Section 5, the data analysis, consists of four parts. Section 5.1 is a description of the way the framework is used as a tool for interpreting episodes of student reflection. It shows how the construct of reflection examined in Section 2 is contextualized within the Earth Structures and Processes unit. Sections 5.2 and 5.3 are two case studies of small groups of students, examining the development of reflective inquiry dispositions for each of five students within the larger participation and interaction patterns of their groups. Section 5.4 re-examines the constructs developed in the case studies, by looking at comparison groups of students from other classrooms conducting the same unit. Section 6 is a discussion of the data analysis, tying findings back into the larger research context laid out in the conceptual framework. The research questions posed above are revisited, and four findings are proposed from the data analysis. Design issues for curriculum and small-group instruction are discussed. Section 7 summarizes the outcomes of the study, situating the findings in the larger research context. Directions are proposed for future work building on the present study.
2) Conceptual framework For at least the last century many educators have had an interest in designing curriculum and instruction for discovery learning – a process through which students actively uncover connections among ideas and construct their own understandings out of these experiences (Bruner 1963; Glaser 1965; Collins, Brown et al. 1989; Lampert 1990; Dewey 1990/1902; Hiebert, Carpenter et al. 1996) The ideas underlying many recent reform efforts (e.g. NCTM 1989; NRC 1998) have their roots in these Progressive conceptions of how learning should happen: active roles for students, facilitating roles for teachers, and a vision of curriculum as an increasingly complex investigation of central themes from the domains. One branch of discovery learning is inquiry-based instruction – classroom investigations of research questions in which students gather and analyze data (e.g. Roth and Bowen 1993; Brown and Campione 1994; Schauble, Glaser et al. 1995). Appropriate characteristics for a “discovery-oriented” classroom project are still hotly debated in academia (Brown and Campione 1997; Hiebert, Carpenter et al. 1997; Smith 1997). Still, one feature of classroom inquiry which most educators believe to be essential is that it involve a process of reflection on the part of students. John Dewey placed reflection at the center of his model of teaching and learning, as a key piece of the process of making sense of experience (Dewey 1933). Reflection, for Dewey, was the connection between ideas and actions, and a key distinction between passive learning of facts and procedures, and a deeper level of experience from which to construct understandings. But what exactly is reflection? 2.1) What is reflection? Reflection ... is a purposeful movement whose end is understanding. And to understand something means to place it in the context of a system. If one is confronted with a topic, then the first thing to do is to resolve it into a question … (Blanshard, 1939; quoted in Hawkins, Mawby et al. 1987, p. 277) Blanshard’s definition provides some useful starting points for our discussion. A “purposeful movement” distinguishes reflection from just continuing along with unthinking or routine activity. The link to understanding something “in the context of a system” implies that reflection can end with a connection between the object of one’s attention, and some organized set of reference points. But what is the “purposeful 10
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movement”? How does reflection lead to understanding? And what does it mean to “resolve something into a question”? Bruner (1996) identifies reflection as “not simply learning in the raw, but making what you learn make sense, understanding it” (p. 87). This process of “making sense” involves “turning around on what one has learned through bare exposure, even thinking about one’s thinking” (p. 88). Reflection, unlike “bare exposure,” somehow makes experience one’s own, investing it with meaning by “turning around” on it. In this section I attempt to unpack the implications of the ways educators have talked about reflection, in order to sketch a model of how the reflective process might work, and why it might be important for learning from inquiry. We need a framework which can enable us to recognize it when we see it, to study the component processes of reflection, and to draw assumptions which can point us toward designs for instruction. The most thorough model of reflection to date was proposed by Dewey in his 1933 book How we think: A restatement of the relation of reflective thinking to the educative process. Dewey’s model of reflection, and its role in learning through inquiry, serves as a starting point for more recent discussions of reflection, its value to education, and how to promote it. These recent expansions on Dewey’s model come from several different quarters: cognitive science, the “critical thinking” movement, and socio-cultural research. We can think of this body of literature as addressing three questions that concern us here: §
What makes a person reflect?
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How do we make sense of things through reflection?
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How do we teach students to be more reflective?
These questions organize the discussion of reflection below. What makes a person reflect? Curiosity, confusion, and “problems”
The act of reflection marks a change in mode of activity, from a familiar, routine mode of work to a more conscious thinking through of the situation. What causes this change to happen? Dewey suggests that the shift to reflection begins with a “difficulty or perplexity”: When a situation arises containing a difficulty or perplexity, the person who finds himself in it may take one of a number of courses. He may dodge it, dropping the
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activity that brought it about, turning to something else. He may indulge in a flight of fancy, imagining himself powerful or wealthy, or in some other way in possession of the means that would enable him to deal with the difficulty. Or, finally, he may face the situation. In this case, he begins to reflect. (Dewey 1933, p. 102) What does it mean for a situation to “contain a difficulty or perplexity”? Situations do not inherently contain these things – rather, perplexity is in the mind of the person experiencing it. Therefore we must look, not to the situation, but to the attitude of the person in it. What might lead a student to be perplexed by a situation? For Dewey, an initial answer to this question is: curiosity. Curiosity is what Dewey called a “native resource for reflection” – an aspect of a person which could lead them, under the right circumstances, to reflect. Dewey proposed a continuum of kinds of curiosity. A basic form is a simple impulse to interact with our surroundings, like an infant putting objects in her mouth, or a youngster “getting into everything” – accumulating experience and raw information about the world. A second level is the more linguistic and social questioning of experience: Why are things as they are? This level of curiosity is based on the realization that “the facts which directly meet the senses are not the whole story” (p. 38). Both of these are predecessors to what Dewey called “intellectual curiosity” – the desire to construct coherent explanations for the things we don’t understand. Curiosity can initiate reflection. When we are presented with a situation which confuses us in some way, we feel unsettled – but just noticing this feeling is not enough to initiate reflection. There must also be “an intellectualization of the difficulty or perplexity that has been felt (directly experienced) into a problem to be solved, a question for which the answer must be sought” (p. 107). This is the beginning of reflection – when a confused feeling has been turned by the mind into a “problem” (see Figure 2.1). This “intellectualization” of a surprising or confusing feeling is similar to what Hibert et al have called “problematizing” (Hiebert, Carpenter et al. 1996). Following Dewey, Hiebert et al see the act of problematizing as the heart of reflection, and as a kind of experience which is often missing from the classroom. Problematizing is not just something that happens by accident, but can characterize a stance toward experience: “[T]hose who engage in reflective inquiry look for problems. They problematize their experiences in order to understand them more fully” (p. 14).
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Figure 2.1. Students problematizing an aspect of an inquiry situation.
Schank’s model of a “dynamic memory” (Schank 1982) suggests a connection between problematizing and one’s expectations in a situation. He suggests that we have “scripts” for common situations we find ourselves in – assumptions about the norms of activity in a given context based on prior experience (Schank and Abelson 1977). When the expectations for a given “script” are violated, we are temporarily at a loss for what to expect, and experience the need to explain the situation. Hiebert’s construct of problematizing differs from Schank’s expectation failure in that students are given more agency in determining whether a situation is problematic. Problematizing may be thought of as the opposite of mechanically following along with a task. It involves pointing out something that is more complex than had been assumed, making the work of completing the task more challenging and mindful. For Hiebert et al, even everyday things in the classroom can be problematized for inquiry. For example, students’ strategies for subtracting numbers – commonly a process of rote application of memorized heuristics – can be made problematic through activities in which students compare different approaches to the problem. In this model, intellectually-stimulating questions do not automatically rise out of a situation (“tasks do not just appear”). Students can learn to make even the familiar problematic. The point is that students have agency in the process: … students should be allowed and encouraged to problematize what they study, to define problems that elicit their curiosities and sense-making skills. (p.12) The first piece of reflection, then, is an act of “defining a problem” – not in the sense of framing an explicit question, but simply by recognizing something that is not understood, and choosing to take an active stance toward resolving the confusion. What happens, then, once students “elicit their curiosities and sense-making skills”?
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How do we make sense of problematic things? Suggestions, remindings, perspectives
Dewey contrasts reflection with “the disposition to pass judgment on the basis of mere custom, tradition, prejudice, etc, and thus to shun the task of thinking” (Dewey 1933, p. 34). We can avoid having a “problem” in a situation by passing these kinds of knee-jerk judgments, and this effectively kills curiosity about the situation. If curiosity is nurtured, however, then problematic aspects of the situation lead to Dewey’s second “native resource” – suggestion. Suggestions are ideas that occur spontaneously in the mind when curiosity has focused us on some “perplexity.” Suggestions may come flooding in by the dozen, or trickling in slowly. They may cover a wide range of ideas about the situation at hand, or be very narrowly focused on certain features. The relationship of a suggestion that arises in the mind to the situation at hand may be superficial, or may involve a deep insight. But the suggestions that arise are the stuff from which we make meaning of the situation. Dewey’s construct of suggestion resonates with Schank’s notion of “remindings” – connections made by the non-conscious mind to prior experiences. Like other case-based reasoning models (e.g. Gentner and Holyoak 1997; Kolodner 1997), Schank’s computerinspired model proposes that when expectations fail, we begin a search through memory for cases which are related in some way to the current, confusing experience. Remindings are the prior experiences which we have “indexed” in memory in such a way that they match the “indices” of the current expectation failure. These remindings are “returned” by the search for relevant clues. What happens next, when we are reminded of something, or an idea suggests itself in our minds? Meaning is made through the process of sifting through suggestions that arise, and selecting, examining, and re-shaping these suggestions until the mind comes to a state of resolution. This process may be conscious and orderly, or it may be instantaneous and sub-conscious. For Dewey, becoming more reflective means developing more orderliness of both the suggestions that arise, and the process of sifting through them. For people who are adept at reflective inquiry, suggestions arise and are worked through in “a single steady trend moving toward a unified conclusion” (p. 47). The case-based reasoning model represents the process of meaning making as one based on analogy. Cases from prior experience are retrieved if analogies can be drawn between cases – i.e. matching the relevant “encoded” features of the current, confusing experience, with similar indices attached to prior cases. If the initial search for matching cases fails, then the goal for understanding rises to a higher priority – this may initiate a
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re-indexing of the current case, or even of prior cases that come close to matching. The incremental search and re-encoding process is one representation of the act of making meaning. Another way of thinking about this process of working through suggestions, or remindings, is as a number of different perspectives from which to re-consider a problematic situation. Hawkins, Mawby and Ghitman (1987) describe “critical inquiry” as a process based on the act of reflection: … to stand back from a topic or problem and reflect on it from a variety of perspectives ... active development of a question or problem, and exploration of information in order to find an answer or develop a connected, meaningful perspective. (p. 277) This is a larger-grain explanation of the same phenomenon of reflecting on a situation. A variety of perspectives are tried out, and a “connected, meaningful perspective” is actively developed – just as the initial problem was actively developed. The term “stand back” also suggests temporarily altering one’s perspective – literally or figuratively – in order to consider ongoing activity from a different vantage point. Multiple points of view can then be synthesized into a new understanding of the situation, much as we triangulate among points to identify a location in space. Collins and Brown (1988) also equate reflection with adopting multiple perspectives on a situation – in this case, an action or a performance. By creating multiple representations of an experience – for example, videotaping a tennis stroke and watching it later; having a tennis coach model motions of the arm, or point out particular angles from which to view – we enable ourselves to look at the experience from different perspectives. The goal of this reflection is to make our “automatic” motions problematic, understand them anew from multiple perspectives, and then synthesize these perspectives into a new understanding, a new performance. How do we teach students to be more reflective? Developing “native resources” and “dispositions”
These characterizations of how we reflect leave us with the question: How do you teach someone to do this better? We are, after all, in search of design implications. What is involved in becoming more reflective, and how do we promote that development as educators?
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Need to develop dispositions, cultivate “native resources”
Dewey believed that teaching students to think reflectively involved cultivating the “native resources” of students’ personalities mentioned above – curiosity, suggestion, and orderliness. Each of these resources appears differently in each individual, as each student has a unique personality and unique thinking dispositions. The goal of instruction is to shape the native resources of each student to become more reflective: Training is that development of curiosity, suggestion, and habits of exploring and testing, which increases sensitiveness to questions and love of inquiry into the puzzling and unknown; which enhances the fitness of suggestions that spring up in the mind, and controls their succession in a developing and cumulative order; which makes more acute the sense of the force, the proving power, of every fact observed and suggestion employed. (1933, p. 55) If education involves developing students’ “sensitiveness to questions” and “love of inquiry,” it is clear that Dewey saw this learning as a process of developing new habits and dispositions, not just acquiring new abilities and strategies. This resonates with the concept of developing “habits of mind” for inquiry in a given domain, such as Perkins, Jay and Tishman’s (1993) dispositional conception of intelligence. This theory of dispositions goes beyond the uni-dimensional construct of ability which underlies many theories of “general intelligence.” Perkins et al’s dispositional model of intelligence consists of three elements: inclinations (a person’s felt tendency toward behavior X, when the opportunity or need is identified), sensitivities (a person’s alertness to an occasion to do X), and abilities (a person’s actual capacity to follow through with X behavior). The dispositional view is valuable for our model of reflection: we want students not only to be able to reflect, but also to have a tendency to reflect of their own accord. The emphasis is on the way the student orients herself toward experience, in addition to her capacity to exercise certain thinking skills. This is different from how we might think about teaching or assessing a particular skill or ability: the kind of prompting required to isolate the exercise of a reflective ability (e.g. asking a student to try to think back to any similar experiences she might have had in the past) obscures to what extent the student might have stepped back from activity herself to generate this kind of question without prompting. This idea of developing a reflective “disposition” is similar to what Bruner called “the attitude problem” of how to teach for learning through discovery (Bruner 1965):
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How do you arrange learning in such a way that the child recognizes that when he has information he can go beyond it, that there is connectedness between the facts he has learned with other data and situations. He must have the attitude that he can use his head effectively to solve a problem, that when he has a little bit of information he can extrapolate information; and that he can interpolate when he has unconnected material. Basically, this is an attitudinal problem – something that will counteract the inertness in that he will recognize the material that he has learned as an occasion for moving beyond it. (p. 103) As with Perkins’ construct of “sensitivity,” Bruner recognizes the importance of the child “recognizing” something in the situation. Rather than talking about an “inclination” to act (which might sound a bit deterministic), Bruner suggests the more malleable construct of “attitude” toward situations. Still, we all know that changing someone’s “attitude” is not so easy either! How do we, in Bruner’s words, “arrange learning” in a way that will “counteract the inertness”? Balancing active roles for students with designing productive domain investigations
Dewey’s discussion of teaching methods for reflective inquiry suggests that educators should focus on shaping the environment in which students work. He advises us that we should pay attention to “establishing conditions,” “setting up connections,” and “creating problems and purposes” to develop students’ native resources: [T]he problem of method in forming habits of reflective thought is the problem of establishing conditions that will arouse and guide curiosity; of setting up the connections in things experienced that will on later occasions promote the flow of suggestions, create problems and purposes that will favor consecutiveness in the succession of ideas. (1933, p. 56, emphases in the original) Who should be “setting up the connections” and “creating problems”? What about active roles for students? There is clearly an important place for teachers and designers in “establishing the conditions” in which students will, in Hiebert’s words, “define problems that elicit their curiosities and sense-making skills” (p. 12). A central concern with promoting students’ reflection in inquiry situations is the tradeoff between student ownership of activity – which will presumably arouse curiosity – and direction of the activity toward fruitful problems for learning by the teacher and the curriculum – which will presumably make reflection more productive in creating connected understandings. This represents the delicate balance between considerations of the child and the curriculum (Dewey 1990/1902).
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Many teachers provide problems for students to solve with the intent that students will adopt these problems as their own. In Smith’s words, “A great deal of well-intentioned teaching has relied on problems that are presumed to be problematic for students, but arguably are not” (Smith 1997, p. 23). Smith suggests that students must play the primary role in generating the problems to be solved in the classroom if problematizing is to be a fundamental design principle. However, for Smith, basing domain studies on students’ problematizing raises a host of problems: “Problematizing, if pursued seriously, will burst the boundaries of the traditional school mathematics curriculum” (p. 22). Problems posed by curricular materials (rather than Smith’s “well-intentioned teacher”) have the additional problem that both the teacher and then the students must adopt the problem as their own, creating two potential levels of disconnect between the intended problematizing and students’ actual experiences. However, teachers often rely upon curriculum to provide exactly this type of guidance in designing instruction – i.e., selecting problems that will highlight important concepts from the domain of study. Curriculum designs, then, must negotiate this balance: opening doors to areas in a domain that will reveal the domain’s “ways of knowing” and internal logic, while still creating opportunities for students to actively make situations problematic for themselves. The words of Dewey and Bruner suggest that curriculum and instruction can shape the way students encounter inquiry experiences in a way that will promote reflection. From a curriculum design perspective, this suggests that materials should not necessarily attempt to contain all of the elements of a “problematic situation” within themselves, but should support teachers and students in structuring inquiry activity in ways which will promote reflection as a regular activity. Summary: A preliminary model of reflection in inquiry
From this discussion, we can distill four basic elements of what it means to engage in reflective inquiry, which can serve as a preliminary model, as presented in Table 1 below.
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Table 1: A Deweyan model of reflection in inquiry
1) PROBLEMATIZING (Hiebert et al): Experiencing a sense of confusion or wonderment about something, and resolving this confusion into a more intellectual curiosity, or an active intent to understand it or resolve it §
Curiosity (Dewey - 3 levels)
§
expectation failure (Schank)
2) SUGGESTION (Dewey): Making connections between current experience and prior understandings, in an attempt to make sense of the problematic situation •
perspectives (Hawkins et al; Collins & Brown)
•
remindings (Schank)
??!!
3) COORDINATION: Examining suggestions that arise in the mind or in discourse about this curiosity, and attempting to impose some order or resolution to these suggestions and subsequent experience, to resolve the confusion •
coordination of theory and evidence (D. Kuhn)
•
orderliness (Dewey)
•
analogy, re-indexing (Gentner)
4) HABITS OF MIND (Gardner, Perkins): Over time, developing dispositions to better focus curiosity toward coherent questions for inquiry, better focus suggestions toward potentially-useful connections, and create more orderliness in the process of constructing understandings The discussion this far has been very general. In order to pursue this question further, we need to take a closer look at the contexts in which we are working. We begin by looking at three contexts of inquiry activity in which reflection is meant to happen – deepening our model as we go.
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2.2) Three contexts for reflection on activity with data Starting with the Deweyan model above, we can begin to examine in more detail the kinds of situations in which we want students to become more reflective. Classroom “situations” are complex – they involve many levels at which we can try to understand activity. Much of our talk in educational research assumes one level at which thinking happens, the “dominanat script” of the curriculum (Gutierrez 1993; Gutierrez, Rymes et al. 1995), without accounting for the other contexts of classroom activity where students’ minds might well be occupied. I propose three referential frames for thinking about classroom activity during a given lesson which are important contexts of reflection: the “data context,” the “task context,” and the “role context.” These are three arenas in which the act of reflection in inquiry requires definition. The “data context” is a representation of a mode of reflective domain thinking intended by the teacher and/or curriculum designers. The “task context” is a system of activity in which we hope this mode of thinking will develop, through instruction. The “role context” is a system of individual factors which contribute to a student’s mode of participation in inquiry and other kinds of classroom activity. Before examining each of these three contexts in detail, we should discuss the rationale for characterizing activity in multiple contexts. Rogoff’s sociocultural framework
The identification of three contexts in which to understand classroom activity builds on Rogoff’s (1995) sociocultural framework for characterizing development. Rogoff suggests that learning through activity is best understood by attending to three planes on which development happens: apprenticeship, guided participation, and participatory appropriation . These three planes are supersets of the three contexts of reflection (data, task and role) proposed here. The “apprenticeship” plane deals with the relationship of classroom practices to those of other communities outside the classroom, practices to which students are meant to be apprenticed. The apprenticeship plane “examines the institutional structure and cultural technologies of intellectual activity” (p. 143), as students become adept at using the “cultural tools” of a community. The “data context” proposed below is conceptualized as one instance of this apprenticeship plane – one family of conceptual tools which students are meant to learn to use. In the “data context,” curriculum and instruction attempt to
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build a relationship between the practices of middle school students and the practices of geophysicists – one of many kinds of “apprenticeship” that are occurring in classroom activity. Rogoff’s “guided participation” plane characterizes concrete and observable practices of students and teachers. It serves “as a way of looking at all interpersonal interactions and arrangements” (p. 147) that mediate daily activity. We are concerned here with how students deal with each other, with their teacher, and with the “stuff” they are using – the artifacts of inquiry. Guided participation is ... an interpersonal process in which people manage their own and others’ roles, and structure situations ... in which they observe and participate in cultural activities. (p. 147-48) This plane of analysis is the place where the intended process of apprenticeship to a domain’s way of knowing – embodied partly in curriculum and instruction – meets the “ways of knowing” of individual students. This is where “the rubber hits the road” – where we observe how activity mediates learning. Dispositions, reflective or not, are manifested in activity on the plane of guided participation. The “task context” of reflection, proposed here, is a representation of the guided participation plane. It proposes particular elements of activity which can be observed in order to study reflection. Rogoff’s “participatory appropriation” plane is where we look for evidence of conceptual and dispositional change of individual students. This context interacts with each of the others, as learning is mediated by activity, and also by conceptions of domain thinking embodied in curriculum and instruction. Changes in students’ own understandings and beliefs may become more or less approximated to the domain concepts embodied in the data context. In other words, the extent to which students are actually “apprenticed” to the data context is mediated by their participation in the task context. Thus we look to students’ changing roles in activity – where the “role context” meets the “task context” – as the site of dispositional learning. In the three sub-sections that follow, the constructs of “data context,” “task context,” and “role context” are developed in detail. The “data context” – a domain-centered focus
The “data context” is the family of things and ideas that characterize the “way of knowing” in the domain of inquiry which we want students to learn. The data context is
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a representation of what we want students to think about and figure out: domain concepts, sets of data for them to study, the real-world items which data represent, and models representing all of these things (see Figure 2.2). These make up the declarative facts students are supposed to learn: that volcanoes are formed along subduction zones, which look like this; that earthquakes happen at plate boundaries, which are here; etc.
Figure 2.2. The “data context” of inquiry situations: elements of the domain’s “way of knowing.”
Reflection within the “data context” is the process by which we want students to build a connected set of understandings in the domain. We want them to problematize one element, such as a pattern in a dataset; to use the other elements, such as real-world items and domain concepts, as points of reference for making sense of the problematic pattern; and then to build a meaningful connection among these elements of the situation. For example, a student might wonder why there is a cluster of earthquakes that happened close together along the Japanese coast (problematizing a data pattern). She might think about (or find on a map) what is there in that part of the world – a range of mountains and islands, including Mt. Fuji, and a deep underwater trench (suggestion of real-world items). She might remember, or be told by a group-mate, that subduction zones are where one plate slides under another, making a trench and a mountain range (suggestion of a domain concept). These two “suggestions” might then become connected with the problematic data pattern, forming an initial connection which builds the student’s understanding in the domain. That data pattern becomes linked with the real-world referents and the domain concepts, forming a (potentially) coherent case which can be built upon through further inquiry. This is one level at which we want to promote reflection – so that students will construct
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these kinds of connections among elements of the data context, forming mental models from which they can make sense of data and its referents. E Mt. Fuji, Japan (a volcano on a subduction zone)
A SUBDUCTION = one plate sliding under another
D
Definition of subduction
Coordinates of earthquakes near Mt. Fuji (caused by subduction)
B Graphic representation of one plate sliding under another plate
C Line of earthquakes next to line of volcanoes (evidence of subduction)
Figure 2.3. The Data Context, annotated with particular things students are meant to learn.
This representation of the data context can be used to represent a productive mode of reflection in the domain. For example, Figure 2.3 shows how particular facts about subduction – concrete learning objectives – can be represented in the Data Context. A student should be able to explain the concept (element A) of subduction as one plate sliding under another. She should be able to identify, produce, or use a model (element B) representing this concept – a visual or tactile representation of the relevant elements of subduction (plates) and their interrelations (movement, movement toward one another, one sliding under the other). Furthermore, she should be able to explain how the model illustrates the process of subduction, using other relevant domain terms such as “plate” (connection of elements AçèB). A student should understand that a particular data item such as a pair of coordinates (element D) is used to represent an event such as an earthquake, or a structure such as a volcano. She should be able to use that information to re-represent that data item, e.g. by plotting it. In so doing she should be able to identify its relation to other plotted
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earthquakes and volcanoes (DçèC), and to known places in the world such as Japan or Mt. Fuji (BçèE). In this sense, the data context is not so much a list of concepts to learn, but rather a map of the conceptual territory within which students are to learn to reflect. I call this level the “data context” because learning in this context involves becoming able to make sense of data. This is the context in which many curriculum designers assume students are doing their thinking during a lesson. Learning means building understanding of domain concepts, and becoming accustomed to connecting data with its referents and with abstract concepts. The data context is an important conceptual territory for us to understand as curriculum designers. By analyzing the domain of study, we try to figure out the kinds of connections students will need to make, and then develop the curriculum so that they will make these connections. But we must raise the next question for curriculum design – what should the students do in order to learn these connections? The “task context” – a cognitive-science focus
There are shortcomings of designing instruction specifically around demonstrating these “data-context” connections to students. Within a given inquiry task, students must make sense of the elements of the data context above – data points, domain concepts, etc. However, instead of considering these things only as abstractions, we now consider the role of reflection in shaping learning in the context of an inquiry task. The “task context” starts to attend to the complexity of activity – what are students doing? As designers we are concerned with creating tasks for students which will lead them to make the desired connections in the data context. In the “task context,” we are teaching students how to do things. This procedural learning might include strategies for completing tasks or using certain tools, as well as thinking strategies for figuring things out – how to identify a strong pattern in data, how to explain your assumptions with reference to evidence, how to query a certain computer database. For now, we represent the “task context” by placing two new elements – tasks and strategies – in the center of the “data context” (see Figure 2.4). The two are overlapping, to represent the mutually-constitutive nature of what we do and how we do it – tasks and strategies are hard to separate conceptually. The two are placed in the center of the elements of the “data context,” to show the primacy of tasks in shaping what connections are made among the elements of the data context.
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As we will see, though this model represents a common set of assumptions about learning through inquiry, there are some important pieces missing. However, we begin by examining the assumptions represented by this basic “task context” of inquiry with data.
Figure 2.4. A simple view of the “task context” of inquiry A task-centered approach to research and design: “Learn what by doing what?”
Following Progressive traditions, many inquiry curricula – and much cognitive research – center on designing appropriate tasks for students to pursue in order to learn (Gitomer 1994), with attention to the kinds of declarative and procedural knowledge they will need to develop in order to accomplish the task. The selection of good learning tasks, based in detailed domain analyses, is a central concern of problem-based learning approaches (Hmelo, Gotterer et al. 1997), as well as “cognitive apprenticeship”-style instruction (Collins, Brown et al. 1989). Tasks for inquiry curriculum can be thought of as having two potential kinds of pedagogical goals, which Glaser (1965) called “learning by discovery” and “learning to discover.” The first involves “teaching an association, a concept, or rule which involves ‘discovery’ of the association, concept or rule” (p. 14-15). For this we would need tasks which lead students to uncover the things we want them to learn in a given domain. The second involves “teaching for a terminal objective which is manifested by the ability to make discoveries” (p. 23). For this we would need tasks which give students practice in the kinds of inquiry experiences they would need to do further inquiry in the future. There is a difference between these goals with respect to reflection. For “learning by discovery,” we can think of reflection as the means by which students will uncover the connections which we want them to learn in the “data context”– potentially a more
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effective means than direct instruction, though not necessarily. For “learning to discover,” reflection is the central habit of mind which we want students to develop – not just a good means to a different end (i.e. procedural and declarative knowledge). Learning as acquisition of strategies and meta-strategies
In this second sense – learning to discover – much cognitive research has focused on how to help students (“novices”) acquire the ability to use particular strategies for inquiry which have been found to be effective in the practice of domain professionals (“experts”). This expert-novice research abstracts out of everyday scientific inquiry those thinking strategies that are effective for understanding complex inquiry situations. For example, Klahr, Dunbar & Fay (1990) distinguish between data-driven inquirers who explore only the “experiment space” of a problem, and more reflective inquirers who spend more time exploring the “hypothesis space.” Exploring the hypothesis space is a more effective strategy: stepping back from examining raw data, to consider multiple hypotheses that might be ruled out, or tested strategically. It also involves more reflection than exploring the experiment space, in that more aspects of the situation are made problematic, and more connections must be made in the mind than are required to explore the experiment space. Schauble, Raghavan and Glaser (1993) state that “the specific importance of reflection is its role in consolidating the development of new strategies" (p. 22). Students must stand back from their project work to problematize and evaluate the strategies they are using, connecting them with the perspective of the goals of the inquiry. This body of research links reflection with the self-regulatory skills of maintaining goal-orientation (i.e. “holding in mind the goals and sub-goals [of] scientific discovery”), and self-evaluation during experimentation. (It is worth noting that this un-problematic concept of the “goals” of inquiry assumes that students share the inquiry goals of the curriculum designers – a problem we return to below.) These descriptions suggest the proximity of the concept of reflection to metacognition (Kitchener 1983; Schoenfeld 1987), or the faculty to perceive, monitor, and control one’s own actions, strategies, thought processes and understandings. The relationship of reflection to metacognition is not well drawn out anywhere. However, many researchers (e.g. Kitchener 1983; Schoenfeld 1987; Schauble, Raghavan et al. 1993) differentiate between more active metacognition (i.e. controlling action, monitoring physical activity, tracking decisions and strategies used) and a more reflective metacognition (evaluating
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success and failure of actions, planning actions based on this evaluation, and questioning relationships among plans, goals, and beliefs). Kuhn’s work on characterizing cognitive skills used in inquiry (Kuhn 1989; Kuhn, Schauble et al. 1992; Kuhn 1993; Kuhn 1997) further specifies the kind of metacognitive activity involved in effectively monitoring and controlling one’s progress in inquiry. For Kuhn, the key component of this process is the differentiation between, and eventual coordination of, theory (or current beliefs about the world) and evidence (or current observations in ongoing experience in the world). A difficulty in fully differentiating theory and evidence is characteristic of people of all ages who are not effective scientific inquirers. Accomplished inquirers are able to reflect upon the relationships between theory and evidence, and use each to inform their understanding of the other. For Kuhn, effective coordination of theory and evidence is a process of stepping back from current experience to question its relation to currently-held beliefs, and questioning those beliefs in light of current experience. As in our Deweyan model of reflection discussed above, connections are developed relating patterns of evidence to kinds of theories or beliefs. These connections shape subsequent reflection. So learning in this context is often thought of as the acquisition of concepts and skills, as in the data context above, but also as the acquisition of strategies and meta-strategies. Reflection in inquiry, in this model, may be seen as a process of metacognitive monitoring of activity, evaluation of progress with respect to goals, and periodic reigning in of action for more conscious evaluation. Reflection is important for connecting ongoing activity to the underlying concepts, and for connecting one problem-solving experience to a more general concept of a “strategy.” Problem 1: How do we teach meta-strategies?
This line of research provides many insights into how we think, in particular how scientists think (Dunbar 1995), and how scientific thinking relates to how non-scientists think (Kuhn 1989; Klahr, Dunbar et al. 1990; Kuhn 1993; Schauble, Glaser et al. 1995). Kuhn’s work in particular, through a microgenetic approach to characterizing changes in reasoning strategies and beliefs over time, makes valuable characterizations of the ways people reason for themselves, the internal logic of that reasoning, and the logic of the tasks they are asked to do. This contribution to the cognitive literature is one foundation of the model developed in this study.
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But there is much less clarity in this body of literature about how we teach at this level. Cognitive research has told us much more about the strategies and actions of reflective and non-reflective inquirers, than it has told us about instructional approaches to help students become more reflective in inquiry. For instance, Kuhn suggests that the “[e]xercise of these skills [i.e. coordinating theory and evidence] may be a sufficient mechanism to induce change ... [including] enhanced metacognitive awareness and hence control of these skills” (Kuhn 1989, p. 687) but she also states that work is needed to explore more active instructional approaches. How do we design curriculum and instruction so that these skills are “exercised”? How do we maximize students’ opportunities to develop the ability and propensity to differentiate and coordinate theory and evidence? Similarly, in concluding a detailed account of problems students face in conducting and learning from classroom experiments, Schauble and her colleagues (Schauble, Glaser et al. 1995) propose a list of solutions to each of several problems that students were found to have, such as the following: Concentrate on moving students beyond an initial interest in generating outcomes, toward reflecting about and understanding relevant concepts, relations, and principles. (p. 159) A noble suggestion, but what are the design implications of “concentrating on” this goal? What should the learning trajectory look like, as students move toward such reflection on relevant concepts? The picture of students’ cognitive difficulties in inquiry is considerably more detailed than the implications of those difficulties for understanding how students learn to reflect effectively. One assumption implicit in some of the literature is that the “art” of teaching this inquiry approach lies in selecting good teaching-learning tasks. While the theoretical models may not yet be developed enough to propose a model for teaching, the assumption goes, there is enough understanding of the kind of learning we want to happen to enable us to intuitively design good tasks for instruction. But there is one fly in the ointment here: do we know what a “task” is? Problem 2: What is a task?
A lot of research, and a lot of common wisdom among educators, takes the constructs of “tasks” and “inquiry goals” as non-problematic. We often think of a classroom task as a simple concept. Students are given tasks by the teacher, such as: “Plot these earthquakes
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on the map with stickers.” Students are assessed based on the degree of accuracy with which they complete the task. Tasks may be defined in the lesson plan, the curriculum materials, or the teacher’s spur-of-the-moment decision to assign something. What’s so complicated about that? First of all, “Plot these earthquakes on the map with stickers” does not mean the same thing in every classroom. Academic task assignments such as this one seem to be generic, but they are in fact shaped by a range of factors that make the task simple or difficult, and more or less meaningful, in a number of ways. Doyle (Doyle 1983; Doyle, Sanford et al. 1985) describes the ways that teacher’s instructions, task specifications, materials, and norms of interaction with students make a given curricular task (like plotting earthquakes) more or less likely to require students to think deeply. So when we talk about a task, we may be talking about very different things in different classrooms. Also, the norms of student participation define the task. In one class (or one student group) it might be assumed that each member of the group is expected to plot at least one sticker; in another it might be assumed that all points must be plotted, but it doesn’t matter which group members do them; and in a third class, it might be assumed that it’s alright if no stickers are actually on the map at the end of the period. In one class it might be assumed that students may call the teacher over and question the meaning of the task at length; in another class, it might be assumed that group members may talk to each other, but may not ask for clarification from the teacher; and in a third class, it might be assumed that students must work quietly and independently. These unwritten rules of classrooms make for very different tasks, even using the same curriculum. Tasks are also defined by the tools and materials used to complete them. These artifacts constrain the ways participants might construe the situation, suggesting certain problems while obscuring others. Some cognitive researchers have reconceptualized cognition as a distributed activity (Pea 1992), one which is shared not only across co-participants, but across artifacts as well (Norman 1993; Wertsch and Rupert 1993). Of course this is one of the most important forgotten factors in our “task context” mode – materials – since we are interested in designing artifacts which can impact the kind of thinking that is done in classroom inquiry. By acknowledging that “tasks” are actually defined through the interaction of several other factors in activity, we make the construct of “strategies” problematic as well. The status of an action as a “strategy” is very dependent on the goals of the person doing it. The construct of a strategy assumes that different participants are pursuing the same goal
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– i.e. are doing the same task – but differ in the approach by which they are trying to get it done. But it seems that at least half of the battle is to get different participants to be doing the same task! So a focus on teaching students strategies and meta-strategies must necessarily be very context-dependent. We cannot assume generically-defined tasks; therefore we cannot assume common goals across participants; therefore we cannot assume that the language of “strategies” is appropriate. In short, we have left some crucial players out of our model. There are people and things in the classroom inquiry context that play central roles in shaping the tasks and strategies that we care so much about: students, teachers, materials which support and constrain inquiry work, and the norms of activity within which the task is defined. The “task context” redefined: students, teacher, and materials
In order to study students’ reflection in inquiry work, we need a more complete picture of activity than that provided by the “task context” model above. Tasks, strategies, data points, domain concepts, and the like do not exist in a vacuum. We must define the relevant factors which shape the “problem space” (Lesgold, Lajoie et al. 1992) within which tasks are defined. Our theoretical framework must represent the major factors that shape students’ engagement in inquiry tasks – the things that make it more or less likely for a student to adopt a reflective stance toward a complex dataset. As curriculum designers, we want to understand the role that designed artifacts might play in promoting this process – but in order to do that, we must have a better picture of the factors in the classroom that shape students’ activity. Let’s revisit our model of the “task context” of inquiry. I propose that there are five elements of a classroom activity system that combine to define an inquiry task. Rather than defining tasks as the set of predefined goals, objectives, and assigned actions described in curricular materials and/or a teacher’s verbal charge (such as “Use red and blue markers to draw the plate boundaries that you are sure of and unsure of, based on the earthquake data”), I propose five elements of the activity system that jointly define a task. These are: §
students’ conceptions of the activity they are doing
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action decisions taken by students
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the teacher’s guidance (actions meant to mediate students’ work)
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patterns of interaction among participants in group activity
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§
artifacts and materials used (including curriculum materials such as lesson plans and worksheets)
The task charge described in curricular materials, and the guidance of the teacher, are prominent here, but their meaning is interpreted through the lens of students’ characterization of their meaning in activity, rather than the lens of designers’ intentions. Next we examine each of these proposed elements of our framework, detailing how and why it is relevant to representing the activity system which is the focus of this study: the small group of students engaging in classroom inquiry with complex data. The goal of this representation is to adequately describe the activity context in which reflective inquiry dispositions are developed. Each of these elements of the task context, like those of the data context above, represents something that can be productively problematized by students, as they make sense of inquiry. The graphic depiction of the activity system in which tasks are defined (see Figure 2.5) places a group of co-participants together within the “task context” circle, to suggest that understandings of tasks are co-constructed through activity rather than pre-formed in one student’s mind.
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Figure 2.5. The more inclusive “task context” – tasks as an activity system Students’ conceptions of the task
We have claimed that curriculum designers’ conceptions of curricular tasks do not necessarily define the meaning that those tasks have for participants in activity. The definition of the enacted task, as distinct from the designs embodied in curriculum materials, is emergent in classroom activity. What do students think they’re doing? Conceptions of the task are often explicitly problematized by students – “What are we doing?” The answer to this may change from minute to minute, and may sometimes be difficult for an observer to determine. But it is crucial to identify how students are thinking about their own current activity, in order to track the development of more reflective dispositions. Evidence of students’ conceptions is found in the words they use in discourse, and especially in patterns of engagement in a variety of activities over time. In the data analysis that follows, we will see how characterizing individual students’ participation patterns over time enables us to understand a great deal about their conceptions of particular curricular activities – their personal and negotiated characterizations of tasks. This might sometimes include a student understanding of their current activity that is wholly separate from the curriculum – e.g. gossiping about friends.
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Within this construct, the notion of being “on-task” and “off-task” becomes more nuanced, as we see the range of student conceptions of tasks. The essential approach proposed here is holding the nature of the enacted task problematic for ourselves as researchers, rather than assuming its definition based upon the official curricular script. Having defined the curricular task as an emergent property of activity, we must reconceptualize the cognitive construct of strategy. The term “strategy” implies a combination of actions and goals – what one does in order to accomplish some given end. I propose that we should not assume known goals of activity, and that we should instead attend to the relationship between what is observably done (action decisions), and students’ apparent conception of goals underlying these actions (conception of task). Action decisions
Action decisions and the talk around them often reveal a very domain-irrelevant conception of the task, but one which we nevertheless want to be able to represent. Also, students’ action decisions sometimes suggest approaches that are relevant to the domain in unexpected ways, different from the strategy intended in the curriculum or instruction. The actual actions taken by participants in activity provide evidence of how they conceive of their current task. Action decisions, often negotiated explicitly in the group, are a common focus of reflection – something that can be problematized in the process of making sense of activity. In this sense they are an important part of this context in which reflective dispositions can develop. Becoming more reflective can include a greater tendency to hold action decisions problematic. This framework has several benefits. For one, it allows for the fluid and co-constructed nature of the meaning of classroom tasks – students’ action decisions over time add up to an evolving understanding of “what we are doing.” A less-problematic “task-strategy” framework leads us to assume that all students “plotting earthquakes” believe that they are plotting earthquakes, which is manifestly not so. Secondly, by focusing on the constructed meaning of tasks in activity (rather than only the intended), we have a more balanced view of the work of curriculum design. Studying action decisions and characterizations of tasks around our designed materials gives a broad picture of how learning can happen. Given the improvisational nature of classroom activity, we are well-served by understanding a wide range of task-conceptions that can
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be enacted around our materials, rather than only the extent to which the intended taskconception was or was not realized. Teacher guidance
Whether she is present at a given moment or not, the teacher shapes the construction of the meaning of tasks in many ways. She is one participant in activity, but moreso, she is a dominant force affording and constraining many kinds of participation by students. For a study focused on teacher-student interactions, the “Teacher guidance” element of the task context might become a context in itself. Most aspects of students’ group experiences – down to the actual constitution of each group – are mediated in some way by the teacher. In this study of small-group inquiry activity with data, the “Teacher guidance” element represents those interactions with the teacher that mediate how the group conceives of the inquiry task at hand. The teacher’s interventions themselves can become a focus of student reflection. What she says can be problematized by students (“What did she mean, ‘Tell the story of the plate?’”), or can be referenced later in making sense of a some other problematized element (“See, that’s like when she said it was going under”). On the other hand, they can follow the teacher’s guidance as they understand it, without making it problematic. The framework for this study represents teacher guidance as a series of interactions with student groups that can mediate reflection, and also the process of developing domain-relevant reflections on the teacher’s guidance. Group interaction patterns
As Doyle (1983), Hiebert et al (1996), Stigler and Hiebert (1998), and others have shown, the norms of interaction among participants mediate how problematic students might find a given concept, task, or artifact. Examples of this mediation often illustrate how the teacher’s norms of engagement of students, embodying her expectations for activity, promote or constrain problematizing on the part of students. But it is important to note that this is true for emergent patterns of interaction among students as well, not just the “official” norms of the classroom. Just as there are global norms of participation in a given classroom, greatly mediated by the teacher, there are also normative patterns of engagement in ongoing student-group interactions that promote and constrain reflection. These emergent norms of small-group practice are constantly being negotiated and evolving, mediated by the teacher, by the students, and by the artifacts used in activity.
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These emergent interactional patterns can be considered “norms” in that they are implicitly imbued with a certain value by the group as it adopts them. In a group with an interactional pattern of always joking, serious discussion may be explicitly devalued and ridiculed as a violation of the unwritten norms. Like more explicit “official” classroom norms, such as “All students are expected to contribute at least one question,” smallgroups’ emergent norms can also be identified, such as “We’re not supposed to disagree about action decisions.” The data analysis that follows will illustrate how these interactional patterns can be reflected upon by students; how they mediate conceptions of tasks and artifacts; and how they mediate conceptual learning. Group interactional patterns are an important element of the task context of reflection in inquiry. Artifacts: materials and tools
Finally, we come to the actual “stuff” of the curriculum: designed artifacts, tools and materials which students work with. I introduce this element last, to underscore the departure intended here from a curriculum-dictated framework for studying classroom tasks. My claim is not that designed curricular materials are irrelevant to activity and learning, but rather that they must be understood in their proper relationship to the process of learning through activity. They constitute one element among many that mediate students’ construction of the meaning of tasks. In research frameworks for studying the effects of curricular designs on learning, we often equate the curriculum materials with some others of the distinct elements of activity which I have separated here: e.g. tasks, data items, data patterns, domain concepts, and models. The data analysis that follows will show how the relation of particular artifacts to students’ conceptions of tasks, and to the intended domain of inquiry, is always problematic. Establishing connections between curriculum artifacts and the abstractions of the data context is a goal, not a given, of instruction. Artifacts as material, cultural and cognitive entities
By artifacts, I mean the material things used by participants in activity – worksheets, books, computers, pencils, tables, etc. The materiality of these things can become a fuzzy line, as highlighted by computer-based examples. On a computer screen, a colored map can be physically present in the room one minute, and gone the next – a “virtual” artifact. But this “virtual” property is not unique to electronic artifacts. Other physical artifacts can appear and disappear, such as a model of a subduction zone made by a
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student’s two hands held together. Words written on a page or on an overhead are also artifacts that can be pointed to and manipulated, but whose materiality can be blurred as they become referents of spoken words, shorthand representations, etc. Material artifacts can blend imperceptibly into being cognitive and cultural constructs through the ways they are referenced in activity over time (Brown, Collins et al. 1989). Pea (1992) has proposed that thinking is “distributed” across people and artifacts in a situation, with significant parts of cognition offloaded onto the things we use. Norman (1993) frames this as “cognition in the head and in the world”: the design of everyday things greatly influences the kinds of thinking we do, affording certain kinds of activity and thinking, and constraining others. Wertsch and Rupert (1993), expanding on the work of Vygotsky and Leont’ev (Wertsch 1985), describe this sharing of cognition between ourselves and our stuff as mediation. Human activity is not “shaped” deterministically by tools, but neither is it “shaped” solely by ourselves as agents. Instead, activity – including thinking – is mediated by both agents and tools. Rogoff’s (1995) characterization of the guided participation plane makes clear the importance of artifacts in mediating activity. On this plane we are looking at “the arrangements between people, including the availability of particular resources and constraints” (p. 148) – resources and constraints that are built into particular “cultural tools.” The tools are cultural, rather than generic or universal, in that their meaning is constructed through activity. These culture-referenced ways of thinking about artifacts can help us understand the role that our curriculum designs play in classroom learning, particularly in the development of reflective inquiry dispositions. An artifact – such as a lesson-plan page or a worksheet assigning students to do some particular thing – is not a task. It is rather an item which can be introduced into the classroom activity system, as part of a teacher’s effort to lead students toward a particular conception of a task. Participants give the worksheet meaning as part of their larger patterns of making sense of activity. For the worksheet to become part of activity that results in students reflecting about plate tectonics, we would expect to see students problematize the worksheet in some way, and build connections between the worksheet, the larger task context, and elements of the data context. Artifacts, then, are not tasks – nor are they data. A page full of latitude-longitude coordinates, or dots on a map, is not a list of earthquakes until participants in activity make it so. Students’ conceptions of what they are doing can afford thinking about the dots as earthquakes, in which case reflective sense-making around artifacts in the task
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context has connected with domain-relevant sense-making in the data context. But until this happens, our carefully-designed dots are not earthquakes. Artifacts and intersubjectivity
Artifacts in the task context include not only the things students use, but also the things they make. It is in the process of turning received artifacts (the “inputs” of curricular activity) into finished work products (or “outputs”) that we hope students will learn (New London Group 1996). These outputs may be as simple as worksheets with answers filled in, or they may be as complex as displays showing a series of student-designed inquiry questions, procedures, and findings. Bruner (1996) sees a special importance of the artifacts students make in mediating learning. They can serve to “externalize” students’ thinking. He describes “the externlization tenet” of educational culture, as a subset of all cultural activity: [T]he main function of all collective cultural activity is to produce “works” … that, as it were, achieve an existence of their own…. Works and works-in-progress create shared and negotiable ways of thinking in a group… Externalization produces a record of our mental efforts, one that is outside us rather than vaguely ‘in memory.’ … thinking works its way into its products. (p. 22-3; emphases in original) The works that students create are invested with their understandings. This makes them important objects of reflection – students problematizing their own works are in a position to revisit their own understandings invested in them, building connections between the task context, the data context, and their own conceptions of the world. Collins and Brown (1988) also give artifacts a privileged place in their discussion of reflection. They point to the value of an artifact which represents a past performance – e.g. a videotape of a tennis swing – in affording reflection on past action, especially with the help of a coach. Instruction involves helping students reflect upon the understandings which are embodied in their inquiry artifacts. Artifacts can become the focus of intersubjectivity of teacher and student – or of student and student. This intersubjectivity defines what Vygotsky called a “zone of proximal development” (Rogoff 1990), a space in which learning can take place, in which moreable and less-able perspectives can become one joint perspective. This space is
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constituted in part by the artifact itself – meaning is mediated by it. So we should try to create – and have students create – artifacts which mediate reflective conversations. Artifacts also mediate students’ process of remembering what they are doing from one day to the next – affording intersubjectivity for an individual across a span of time (e.g. intersubjectivity between me yesterday, and me today). Artifacts mediate the flow of activity and sense making over time, especially in the case of extended inquiry projects. When the students go home, they often leave their thoughts about plate tectonics behind in the classroom, along with their lab notebooks and their clay models. When they come back the next morning, they look at the “stuff” they left behind, and they must answer the question: “What were we doing again?” Similarly, once students have finished their report on the Himalayas, they may or may not return to thinking about the Himalayas ever again. If we want them at some point to come back to any of these ideas, we are well-advised to rely on physical artifacts to help them find the thread connecting today’s activity to last week’s Himalayas report. When a situation is problematized by a student, artifacts can prompt some of the “suggestions” that come to mind – the more students’ understandings are represented in their work products, the more valuable this reflection can be for learning. The artifacts may change in the students’ eyes over time as well, becoming “problematic” where they once were not. Summary: the place of artifacts in the conceptual framework
Artifacts, then, are potentially very significant mediators of learning. Their value should be assessed in terms of the extent to which they are problematized by students, invested with domain-relevant meanings, and incorporated into conceptions of that day’s task that involve the data context. This is in contrast with viewing artifacts as agents in the classroom which cause learning, or fail to cause learning. Since artifacts are incorporated into cultural practices, we must disentangle our understanding of the affordances of their designs from our understandings of the other mediators of the cultural practices themselves (Stigler and Hiebert 1998). The construct of a “task context” (rather than simply a “task”) is meant to help us disentangle artifacts from other mediators of sensemaking. Task context summary
In summary, I propose that inquiry tasks are not generic, and that their definition arises from participants in activity. A given task’s meaning, including its underlying goals and
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objectives, is created by students as they conduct the activity. It is constituted by their individual conceptions of what they are doing, the actions that they take, the teacher’s guidance, their norms of interaction in the activity system, and the material artifacts they use. Each of these constructs is defined in terms of the others, and together they define the observable slice of activity that we consider a curricular task. This “task context” framework is used in thie present study to identify more and less reflective modes of engagement in activity with people and things. In Rogoff’s words, Instead of studying individuals’ possession or acquisition of a capacity or a bit of knowledge, the focus is on the active changes involved in an unfolding event or activity in which people participate. (Rogoff 1995, p. 151) The five elements of the task context are representational tools for characterizing “changes in an unfolding activity,” without limiting ourselves to the assumption that activity is related in a particular way to our domain analysis, or to particular modes of thinking (i.e. scientific reasoning). We can analyze participation in activity, including but not limited to the exercise of particular reasoning strategies and meta-strategies. The constructs of the task context provide the basis for characterizing activity, and changes in patterns of activity over time. However, in order to characterize students’ learning over time, we need a representation of their states of knowledge, abilities, and dispositions. The representation of learning for a given student lies at the next level: in the “role context.” The “role context” – defining learning from the learner’s perspective
The “role context” expands outside of the task on the table, or the current focus of activity, and examines the elements of a student’s subjective experience in the classroom which are likely to shape her participation in the activity system. At this level we can characterize change in individual students, in relationship to the ongoing patterns of activity in the “task context.” Developing new roles and dispositions in inquiry activity
In the task context, we defined activity in terms of patterns of interaction between people and artifacts. But beyond these observable actions of students and teacher, there are invisible factors that shape the nature of students’ participation in classroom activity. These are the elements of the “role context” of classroom activity. It is in this context
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that we look for changes in student activity that would suggest the development of dispositions and understandings. I will discuss five elements of the “role context” of classroom inquiry here, and these will lay the groundwork for the characterization of changes in student participation – i.e. development of more reflective dispositions – in the data analysis section below. The elements are: §
Students’ conceptions of classroom norms: “How are we supposed to act?”
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Student roles, or participation patterns in activity: “What do I do?”
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Student identities: “Who am I?”
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Student understandings and beliefs: “What do I know?”
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Prior experiences: “What’s happened before?”
Each of these elements shapes students’ tendency to be more or less reflective in classroom activity, as represented in Figure 2.6, and in the discussion below.
Figure 2.6. The role context: Factors influencing individual students’ dispositions in classroom activity Perceived norms of classroom activity
Every classroom has its own unwritten norms of activity – implicit cultural rules by which members of the class make meaning of the language of task assignments. Classroom norms answer the implicit question, “How are we supposed to act?” These
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norms determine who is expected to talk, when, and how; what is “good enough” work, from whom; what behavior is acceptable and unacceptable, from whom; etc. Classroom norms, more than any designed curriculum artifacts, shape what kinds of products students are likely to create; what kinds of discussions are likely to happen; and ultimately, what kind of learning will take place. Some of these norms may be explicitly discussed, even written down; some are dictated to students by the teacher or the school administration. Many norms are determined by the cultures and sub-cultures which intersect in the classroom (Bronfenbrenner 1979), and may well be invisible to all participants within those cultures. However, other norms of activity are co-constructed by the participants in a classroom on a daily basis. All participants in activity co-create the classroom’s norms of participation, through their interactions. Some of these norms are explicit, but many are not – participants are often unaware of the unwritten rules by which they interact on a daily basis. Hiebert et al (1996) point out that the cultural norms of the classroom ultimately determine the extent to which a problem has reality for students: We propose that reflective inquiry and problematizing depends more on the student and the culture of the classroom than on the task. Although the content of tasks is important, the culture of the classroom will determine how tasks are treated by students … Given a different culture, even large-scale real-life situations can be drained of their problematic possibilities. (p. 16) Norms of activity shape student reflection in a number of ways. They determine to what extent stepping back and thinking through a problem is acceptable classroom behavior – this kind of questioning may be highly valued, or it may be thought of as evidence of stupidity, not knowing the answer. Norms determine what kinds of things may be considered problematic – is it OK to question the logic of a domain concept we’re supposed to learn? They also determine how the artifacts of inquiry work are likely to be thought about – is our data map something we should keep after it’s finished, to look back at if we need it later? In this way norms of activity greatly shape opportunities for reflection in classroom inquiry. Classroom norms are not a focus of the data analysis per se. However, students’ conceptions of these norms – that is, students’ characterizations of the patterns of activity they perceive around them – do play a significant part in shaping the roles that are adopted. These conceptions are not norms in the sense that we usually refer to: explicit terms of engagement and modes of participation encouraged in classroom activity (Kagan
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1992; Hiebert, Carpenter et al. 1996; Stigler and Hiebert 1998). But I use the term “norms” because this distinction may not be meaningful to students – the patterns of activity that see and react to are their conceptions of the valued practices of the community. In this sense, in the individual’s role context, perceived norms are what matters. Student roles in activity
As norms of activity are co-constructed, all participants adopt their own roles in that activity. These roles are shaped by the classroom norms, and in turn they shape norms as well. Every teacher knows the extent to which even a single student’s mode of activity can shape the definition of “acceptable behavior” in a class – for better, or for worse! Roles of participants change over time, and vary across types of interactions. A student, teacher, or researcher in a classroom may adopt several different roles over a 15-minute period. Some roles are explicit, and even designed beforehand – such as the role of “Reporter” for a cooperative-group activity. Other roles are adopted implicitly or subconsciously – such as the role of “Tension-Breaker” when a student makes a comment that keeps another student out of conflict with the teacher. A student’s role is their implicit answer to the unspoken question, “What do I do?” The role a student adopts in a given mode of activity is a manifestation of her disposition toward that activity, at that point in time. Becoming more reflective in inquiry means adopting roles that include making things problematic, and seeking connections among elements of the inquiry situation. Many common roles which students play can preclude reflection – while other roles, which might not be thought of as “academically successful,” can provide surprising opportunities for reflection. For example, if a student is playing a brainy role of “She Who Knows the Answers,” this role may make it unlikely for her to step back and puzzle over something confusing. A student who is playing a jokester role of “Comic Relief Provider” for his group will probably be constantly on the lookout for ridiculous or anti-school connections to the current activity, but perhaps not for connections to domain concepts, personal understandings, or data patterns. A student who is playing a resistant role of “Teacher Challenger” might be very likely to notice inconsistencies in a domain concept explained by the teacher – an opportunity for reflection, as the concept is made problematic. Her role in this situation might allow for reflective connections between the explanation’s inconsistency and her own understandings about the world – or it might lead her only toward confirmation of the teacher’s flaws.
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In these ways, students’ roles in activity are closely tied to the development of reflective dispositions toward inquiry with complex data. Student roles shape group interactions as well, and in turn shape other students’ roles. These two constructs – norms and roles – shape the ways that students think about everything within the “task context” and “data context” discussed above. Of course, norms and roles do not exist in a vacuum either. Student identities
The role that a given student adopts in activity is shaped not only by the classroom norms, but also by their own identity, or sense of themselves. Fuson (personal communication, 1998) relates the development of productive roles in classroom activity to the development of a student’s self-image as one who can participate in meaningmaking activity. Learning, in the largest grain, is a process of changing identity. A student’s sense of self in the classroom is tightly interwoven with all the other contexts in which she has an identity – her cultural and ethnic identities, her family identities, her peer-group identities, and her identities in a host of other socio-historical contexts of which she may not even be aware (Wertsch 1985). Each of us inhabits many different “life-worlds” (New London Group 1996) in each of which we have ever-developing and inter-connected identities. The construct of identity answers the question, “Who am I?” Identity and role in classroom activity are clearly tightly connected, and they influence each other. If a student sees himself as a smart and capable boy, one who deserves recognition, he is likely to adopt a role in activity in which to achieve success and be recognized for it. If a student sees herself as an instigator of conflict, one who doesn’t take shit from anybody, she is likely to adopt a challenging and confrontational role in classroom activity. Conversely, the roles a student assumes in classroom activity can shape their identities in other contexts. If a student has great success playing a clever joking role in the classroom, this may shape her sense of self in other contexts as a funny and entertaining person. If a student finds that he can identify interesting anomalies in data sets in a series of activities, he may more frequently adopt the role of “Pointer-Outer,” making spontaneous observations to his group. This in turn may shape his sense of self in other contexts as a person who may notice things others do not. Learning has been described as development of an identity of mastery with respect to the practices of a community (Lave and Wenger 1991; Rogoff 1994). This definition makes clear the tight relationship among identity, role in activity, and learning. These
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connections between role and identity are where we develop our long-term learning goals for students – not for acquiring particular skills or bits of information, but for becoming a more confident and able person. In the present study, the big-picture learning goal for students is to develop a sense of themselves as one who can look at a complex bunch of information, identify interesting problems, and figure them out. This is what it means to have a reflective disposition with respect to inquiry with complex data – at a level above the particular strategies required for analyzing a particular dataset. Student beliefs and understandings
An important aspect of a student’s identity, and one that shapes the roles she will play in classroom activity, is her sense of what she herself knows, believes or understands. This may be thought of as her epistemological identity, or sense of herself as a “knower.” This identity shapes understandings and beliefs, asking the question “What do I know?” One’s own beliefs and understandings can provide valuable material for reflection, assuming a role and an identity which allow one to reflect upon them. The more a student has developed her own understanding of a domain or a phenomenon, the more material she has to work with in making sense of complex data during inquiry. If she has heard and thought a lot about volcanoes, the information she already knows can be a valuable resource in figuring out concepts and data patterns encountered during inquiry. On the other hand, some of her understandings may make it more difficult for her to figure something out – for example, if she believes earthquakes happen only on land, she may get confused when she has to plot earthquake data in the ocean. This confusion can be problematized and lead to reflection – or it can be dropped and lead nowhere. Cognitive research has explored students’ understandings and beliefs in relation to accepted domain concepts – comparing “folk understandings” of “novices” with “expert understandings.” In the framework proposed here, I conceive of this comparison as the relationship between a student’s understandings, and the understandings embodied in the data context. The point of instruction is to change each student’s understanding of the world, in such a way as to create observable mappings between that understanding, and a coherent set of understandings which is valued by a community of inquiry. Of course beliefs and understandings exist on many levels other than the domain of inquiry. The representation used here for “beliefs and understandings” lumps them all together within one construct. This is not to minimize the importance of understanding the complexities of how students see the world, but rather to suggest that these beliefs and understandings are one of several elements which jointly constitute students’
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performance in class. They must be understood in the context of the other elements of the role context. Prior experiences
Prior experiences shape all of the other elements of the role context: one’s conception of classroom norms, one’s own roles in activity, one’s sense of self, and one’s own beliefs and understandings. Each of these things represents the cumulative history of a student’s prior experiences, both within and outside of the classroom. Prior experiences shape understandings and beliefs. A student who has lived in Los Angeles, or has visited family in Mexico City, may understand what an earthquake is in an immediate and personal way. Another student who has made a “continental drift” puzzle in 3rd grade may understand what a tectonic plate is, in another way. These prior experiences are potential “targets” for making connections when a question or confusion arises during inquiry activity (Dewey 1933; Schank 1990). They can provide a bridge between current experiences in inquiry activity, and the student’s own understandings – a student may be reminded of a prior experience, and in the process make a connection between the earthquake data in front of them, and their own knowledge that earthquakes can happen in Mexico. Prior experiences also shape how students perceive, and contribute to, the norms of classroom activity. They provide the expectations on which these norms are based, and thus also shape the roles students are likely to adopt. What has happened before provides “scripts” for activity over time (Schank and Abelson 1977; Gutierrez 1993; Gutierrez, Rymes et al. 1995). Prior experiences have the potential to be valuable resources for reflection, depending upon a student’s conception of a given task, her role in activity with respect to reflection, and the norms of the class and the group in terms of relating classroom realities with other contexts. Summary of the role context
The long-term goal of instruction in the role context is not just the development of new roles in classroom activity – it is a positive change in a student’s sense of self, in particular their identity as a knower and as an inquirer. The construction of a series of experiences to support this identity-development is a long-term goal of instruction throughout the school year. Norms of classroom activity are a context in which we hope designed artifacts can help shape the development of students’ “identities of mastery,” not just in the domain of earth science, but in the many contexts of a student’s life.
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Strategies and meta-strategies for making sense of earth science data are only one piece of this larger learning goal, one component of the school year’s experiences. In the present study, the role context is backgrounded, except in its most direct interaction with the task context: the changing roles, or interactive modes, of students as they participate in inquiry activity. Student beliefs and understandings are discussed only in assessing the relationship between their understandings of the domain, and the datacontext understandings intended in the curriculum designs. Student identities and conceptions of the norms of the classroom are mentioned in analyzing their developing roles in activity, but are not a focus of the data analysis. Understanding this identity context of learning is of utmost importance for educational research (Bronfenbrenner 1979; New London Group 1996). Students’ beliefs and understandings (e.g. of scientific inquiry, or of a particular field of study), and students’ conceptions of classroom norms (e.g. ways students think about group work), are often treated in the research literature as separate from the constructs of identity, prior experience, and role in activity. These approaches are valuable for the light they can shed on patterns of student thinking and understanding, but do not provide an ecologically complete perspective. The interactions among the constructs proposed here can give a fuller picture of how patterns of understanding and sense of self mediate the processes of learning through activity. 2.3) Summary: A framework for studying reflection in inquiry The three-context framework outlined above provides constructs necessary for analyzing students’ interaction with, and learning from, a curricular unit. The framework has been emergent in the study presented here, informing and being informed by the evolving understandings of what students were learning, how, and why. The top-level instructional goal for the unit – furthering the development of reflective dispositions for investigating complex data – required an analytical framework for tracking dispositional change. Furthermore, it required a framework which could at once represent particular domain understandings, and also particular students’ identities. These two points of reference come together in the daily practices of classroom activity. The constructs of “data context,” “role context,” and “task context” are meant to account for these three considerations. We hope to see the development of reflective participation patterns in the task context, and the adoption of more reflective roles in the role context. This will also correlate with
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increasingly domain-relevant conceptions of curricular tasks, indicated by increasing reference to the data context in reflections on data. The framework requires consideration of all three (Figure 2.7).
Figure 2.7. Three contexts of reflection in classroom inquiry with complex data.
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3) Design of this study: research methods This section describes the methods used for studying activity. Four aspects of methodology are addressed here: §
Description of the research sites and participants
§
The level of analysis for studying activity
§
The data collected
§
The process for analyzing the data
3.1) Research sites and participants: three classrooms studied Enactments of the curriculum were studied in the classrooms of three teachers at three different schools, in order to identify affordances of the curriculum designs in more than one context. The first of the teachers, Jennifer Mundt-Leimberer, has been a collaborator with the SIBLE project for several years. She was a co-designer of the unit, and the only teacher who carried out every phase of the unit with her students. The other two teachers, Jeni Olson and Thea Raedeke, were volunteers identified through their schools’ participation in the Center for Learning Technologies in Urban Schools. They are the first two teachers who expressed an interest in enacting a unit on plate tectonics, and each subsequently agreed to conducting a full study of the enactment in one or more of their classes. Data from these classrooms are used to expand on the analysis of the case studies from the Boone classroom. The three teachers, and two of the three primary researchers involved in data gathering, are white. While variables of culture and ethnicity are not explicitly studied here, the cultural nature of the construct of reflection suggests that this mostly-white research team might create a cultural skew of assumptions and interpretations. Future work on this model would benefit from an intentionally cross-cultural research design. Classroom 1: Daniel Boone Elementary School
Boone is a large, overcrowded school on the north side of Chicago, with about 1,200 students in a building built for 900. The neighborhood it serves is a predominantly immigrant community, with large South Asian, Middle Eastern, and Central European populations. There are bilingual classrooms for several language groups.
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The demographic breakdown of the 7 grade class studied is: 29 students total:
13 girls, 16 boys
US-born white:
24%
South Asian:
21%
European immigrant: 17% Middle Eastern:
14%
African American:
10%
Latino:
10%
Ms. Mundt-Leimberer teaches math and science to this group, as well as to an 8th grade group. The two classes each are in her room for half the school day (alternating mornings and afternoons on alternate days), and that time is divided between math and science. A student teacher worked with Ms. Mundt-Leimberer throughout the unit, leading a few of the discussion activities, though her main responsibilities were for activities outside the unit. Students are grouped into different table groups (five to seven students) over the course of the year. They are also put into various small groups (two to four students) for particular activities – a student might alternate between two or three different groupings in the course of a week’s activities. Classroom 2: Inter-American Magnet School
Ms. Olson teaches 6th grade at Inter-American Magnet, a dual-language elementary school. This means that instruction is conducted primarily in Spanish across the curriculum, at varying levels depending upon grade. In 6th grade, 60% of instruction is in Spanish. For the most part during this study, the teacher agreed to conduct science instruction primarily in English for the convenience of our study, though there were some changes in this arrangement during the course of the unit. We developed versions of some activities in Spanish. The largest population in the school and the focus classes is Latino, with minorities of non-Latino European-American and African-American students. The majority of students in the 6th grade classes are English-dominant. Though it is a magnet school, there is no screening for ability level in admission to the school. Students are drawn from the full spectrum of academic levels of the Chicago Public School system, and academic levels are very varied.
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Ms. Olson, a 3 -year teacher, briefly participated in curriculum development activities with the Center the year before on a different unit, but otherwise had not collaborated with us before this study. Ms. Olson taught the unit to all three of her classes – the school’s entire 6th-grade cohort of students. The classes have between 21 and 24 students each. These three groups of students share instruction among a math-science teacher (Ms. Olson), an English language arts teacher, and a social studies/ Spanish language arts teacher. Ms. Olson has each group for 90 minute periods, which is divided between math and science instruction. The ethnic breakdown of the Inter-American classes is: Latino:
65%
US-born white:
19%
African-American:
14%
Asian:
1%
Data was gathered in two of her three classes, with more extensive data-gathering (including pre-post individual and group interviews) focused on one table group of six students in one class. Classroom 3: Hayt Elementary School
Hayt is a public elementary school on the far north side of Chicago. The population of the school is very racially and ethnically mixed, with a plurality of Mexican-American students being the largest single ethnic group. Ms. Raedeke has taught for six years, five of them at Hayt. Classes are departmentalized, and Ms. Raedeke teaches three 40-minute science sections per day. Each class has 31-34 students. The ethnic breakdown of the classes at Hayt is: Latino:
37%
African-American:
25%
South/SE Asian:
24%
White:
14%
Data was gathered in one of Ms. Raedeke’s three classes, with more extensive datagathering (including pre-post group interviews) focused on one table group of four students.
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Primary focus on one classroom
Ms. Mundt-Leimberer’s 7th grade classroom was the primary site of research, in which additional data about students and instruction was gathered – including data on their use of the Progress Portfolio, which constitutes another branch of SIBLE research. The two case studies presented here are both student groups from her class. Groups from the other two classrooms are used as comparison cases for examining the patterns of activity identified in the Boone study. While I initially intended to study the focus groups in each class for purposes of comparing outcomes, I have chosen instead to examine the focus groups at Boone with a closer lens. It became clear during data analysis that the development of individual roles was an important context to study in the development of the model of reflection. Rather than have superficial characterizations of 17 students’ changing roles, I chose to develop a detailed picture of seven students’ participation. The Boone classroom thus served as the place in which assumptions about activity norms were developed and discussed in greatest depth with the teacher and fellow researchers. These assumptions were then used to look for signs of the same patterns in the other classes’ data, as described in section 5.4. A useful follow-up to the present analysis would be to do tight comparisons of student talk around particular activities across classrooms. This would give valuable insights into the different ways that opportunities to reflect are constructed in different classrooms. For the present study, though, I am trying to characterize the development of reflective dispositions over time. The development of the framework proposed here is a prerequisite to selecting particular dimensions of the model for comparison studies. 3.2) Level of analysis: Focus on small groups In studying classroom activity, we could choose to focus on several different levels of analysis – teacher-student interactions, teacher-whole-class interactions, individual student activity, the small group, the table group, etc. Each of these interactional spaces was found to be a space in which reflection happened, and each is important to understand. The data analysis for this dissertation focuses primarily on the phases of classroom activity in which students worked in small groups at their tables, or at computers. The other main modes of classroom work – whole-class discussion, individual student work, and various modes of teacher-student interaction – are kept mainly in the background.
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Background levels of analysis: Whole-class and individual students
This limiting of data analysis to small-group work was a difficult decision. In each class studied, there were many rich examples of reflective talk in whole-group discussions. In fact, this topic could be another dissertation by itself. These discussions clearly shaped students’ learning very significantly, and were the primary venue in which local learning experiences from the small groups were tied back to larger domain concepts for the whole class (see (Tabak and Reiser 1997) on the role of whole-class discussions in supporting classroom inquiry). The facilitation of these discussions was also a subject of great interest to the teachers I worked with, and to myself as a teacher – there is a need for a deeper understanding of how whole-class discussions can promote productive reflection. However, the nature of these whole-class, teacher-facilitated discussions is such that the thinking of individual students is hard to study. Students are constantly prompted by the teacher to make particular connections between observations and ideas. Discourse moves along quickly, with the teacher making frequent strategic decisions on how to direct the flow. The examples of reflection that can be drawn from these discussions are many, and they are often very impressive in themselves. But each student says few things, even in the longest discussion, and many students remain invisible. Many comments are adventuresome, shot-in-the-dark reflections, and they do not always connect to the ongoing work with data which is the heart of the curriculum unit. This mode of adventuresome thinking and wide-ranging discussion is clearly very important to learning through inquiry, but does not give as clear a view of the relationship between curriculum designs and reflection on data. For these reasons, this rich set of data is backgrounded in the present analysis. Reflection during individual student work is also backgrounded here. There were many instances in which students worked individually in what appeared to be a mode of deep thought, and many examples of individual work products that showed reflective thinking around data. However, individual work does not provide the bread-and-butter of this kind of classroom research: talk! There are many moments on videotape in which an individual student looks intently at a screen full of data and says, “Hmmm!” This suggests that they are reflecting on something, but it doesn’t give us much from which to analyze their thinking processes, so individual reflection is also in the background of this analysis.
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Rationale for studying small group activity
A research focus on small group work is very valuable to researchers and teachers. It is valuable for learning about students’ roles for participation in classroom activity, as these roles are constantly negotiated and co-constructed by students in their “table talk.” It is valuable for teachers, in that the majority of small group work at any one time happens without the teacher being present: while she or he is working with one group, the others are working independently. This research on modes of small group work provides a window on what teachers usually don’t see in the classroom. The level at which I have chosen to study the development of reflective thinking is the level of the small group of two to five students assigned to work together. Some advantages of this level of analysis are: §
A focus on small groups enables us to study peer interactions, a major influence on student activity and thinking, without having to account for all peer interactions in the entire classroom – only the most immediate.
§
Small groups can mirror the ethnic, gender, and academic diversity of the class, giving a micro-perspective on these larger issues. The focus group in each class was set up in this way with each teacher. The analysis of students’ participation in these small groups can shed light on larger issues of diversity and participation in the classroom.
§
Small group work is a common and very useful configuration in classrooms, especially for facilitating inquiry with complex datasets – in the case of computerbased data, small group work is essential. This makes the small-group context for reflection a very useful one for educators to understand.
§
Group-work can be designed – teachers can use design principles such as those in the cooperative learning literature (e.g. balancing positive interdependence and individual accountability (Johnson and Johnson 1982)), and awareness of individual students’ needs, to shape interactions within groups. Therefore understanding how reflection manifests itself in the small group can potentially lead to group-work design principles.
§
We use student discourse as our primary data on thinking, and discourse is coconstructed by nature. Therefore it is often difficult to attribute a particular disposition strictly to an individual, but rather to the interaction between individuals.
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The majority of interactions between students, both academic and social, happened between members of the same table-group. §
Small groups have an observable life cycle in the classroom – they change over time, accomplish milestones, and experience crises. This gives the group-level analysis validity as a research construct, and also makes it easy for teachers and researchers to talk about student activity and learning with a set of shared observations around each group. Group-level events become useful organizers of knowledge about the individual students in the group.
For these reasons, I have chosen to track two to three small groups in each class, which together make up one table group, as they go through the unit. Each individual student is considered at the level of her changing role in group work with data, and each group is analyzed as a context for the development of reflective modes of thinking. 3.3) Data collected In each classroom one table group of four-to-seven students was set up, in collaboration with the teacher, to be a focus group. These groups were made to be representative of the diverse members of the classroom, including ethnic and gender diversity, and a range of academic performance levels. We made a point to include students who tend to talk (i.e. not the quietest students), to ensure enough discourse data to provide evidence of students’ thinking during group activities. A researcher was present for nearly every day of the enactment in the Boone classroom, and for three out of every five days in the other focus classrooms. We gathered six kinds of data during the course of the enactments in each classroom, from which to characterize student activity: field notes, videotape of class sessions, artifacts of student work, videotape of pre-post student interviews (individual and group), audiotaped design meetings with teachers, and videotaped reflection meetings with teachers. Field notes from class sessions
Field notes documented changes in modes of classroom activity, problems and successes with particular lessons, passages of interesting discourse and activity, etc. The field notes were used to focus later analysis of the videotape.
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Videotape of class sessions
Videotape was recorded for every class attended. The camera focused on the whole room during whole-class sessions, on the focus group during group-work time, and on individuals in the focus group during individual work time. (At Boone two cameras were used, to document both computer activity and table activity.) Videotapes were logged with summary information of activity during the period, and later used to generate verbatim transcriptions of discourse during focus activities. Episodes for transcription were identified from the field notes and the tape logs. When table groups broke out into smaller sub-groups of 2 or 3 students, the camera followed one small group from the focus group, selected on the basis of interesting interactions in the groups observed in the class up to that point. Therefore not all smallgroup work was recorded, though we tried to get representative footage of small-group work from each sub-group at the focus table in each class. Artifacts of student work
Photocopies, photographs, and scanned images of the focus students’ work products were gathered: science journals, worksheets, maps, models, drawings, computer files, and other assignments. This dataset was used for triangulating assumptions about students’ thinking around particular activities based on classroom discourse. Interviews with students
Two kinds of interviews were conducted with focus-group students before and after the unit at Boone and Inter-American. (At Hayt only group interviews were done.) Individual interviews were developed to find out students’ conceptions about the earth’s crust, and to prompt them to make observations and explanations from GIS-generated datasets (volcano locations). Small group pre-post activities (3 students each) were developed to observe students’ patterns of participation in group inquiry with complex data. Each activity used different printed GIS demographic datasets, and asked students to make observations from the data, then to use the data to conduct a mini-inquiry task. These two interviews provided information about the following: •
students’ domain conceptions before and after the unit
•
students’ abilities and dispositions to generate questions, observations, and explanations from complex datasets, before and after the unit
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•
students’ roles in working with complex datasets in both a collaborative work context and an individual work context, before and after the unit
The protocols for the individual and group interviews are attached as Appendix A. Audio-taped or video-taped design meetings with teachers
Design meetings with teachers before, during and after the enactment of the unit were taped, and segments were transcribed during data analysis. These tapes were used to characterize the specific instructional goals for activity design and re-design throughout the unit, and to document teachers’ conceptions of the value of particular activities for particular kinds of learning. Videotaped reflection meetings with teachers
At least once during each enactment of the unit, and once after each enactment, I met with the teachers to view selected video-clips and/or artifacts of classroom activity. We discussed observations about individual students’ participation and learning, and successes and problems with the curriculum. These data were used to triangulate assumptions about students’ roles in activity and learning throughout the unit. 3.4) Process for analyzing the data The data analysis process, and the research questions guiding it, changed over the course of the analysis. The conceptual framework was emergent in this process, as assumptions from before the study changed in unexpected ways. The research questions that shape the data analysis here are an outcome of the data analysis process. Discussions with teachers throughout the enactments served as the first phase of data analysis. Notes from these meetings, and my own reflections written down between class periods, provided a list of observations and assumptions to begin analyzing the rich data that was gathered. The theoretical framework presented here developed out of the process of studying these meeting notes and reflection notes, organizing data, and revisiting design assumptions from the unit. Several graphic representations of unit activity in each classroom were created, and used for organizing tapes, transcripts, and artifacts. These helped to identify the “focus activities” for transcribing videotapes, and to select the periods of small-group work with data as the main focus of the analysis.
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The data analysis began with a focus on individual students’ “dispositions,” but this focus was shifted toward a focus on the development of group norms and participatory roles. This change of focus came through reviewing reflection notes and meeting notes – it became obvious that the “real story” of what was going on was at the group activity level. Discussions with teachers about individual students’ dispositions tended to gravitate toward discussions of their interactions with group-mates. A reflection meeting with Ms. Mundt-Leimberer after the unit focused on discussing the changes in individual students’ roles in activity before, during, and after the unit. This discussion, along with a period of video analysis before and after it, helped to solidify the approach of characterizing learning as the development of more reflective roles in group work. Characterizing episodes of reflection was an emergent process too. Initially I looked for examples of student talk that seemed to me like examples of reflection – several had been highlighted in field notes. These episodes were transcribed and discussed with fellow researchers, looking for a coding scheme for identifying reflection in discourse. Other episodes that seemed interesting were thrown into these discussions as well. At first whole-class discussions were transcribed, as they were rich with examples of making connections between the investigation and other perspectives. But these examples were eventually taken out of the “pot” of reflective episodes being analyzed, as the focus on small group work became more central. As the framework for understanding reflection developed, the data were studied for evidence of different “foci” of reflective comments – i.e. things being talked about – and different “targets” of reflection – i.e. external perspectives or “remindings” brought to bear in understanding the focus. From a laundry list of “kinds of things you can reflect on,” the constructs of “data context,” “task context” and “role context” emerged. These constructs were then used to look back through the data for evidence that they shed light on group activity. I matched the frameworks of Dewey, Rogoff, and Kuhn to the developing model of reflection repeatedly, to try to understand how their frameworks shed light on the data from the study. Revision of the curriculum materials was ongoing through the enactments and the data analysis for this study. This helped to keep the design analysis directly in the mix – realizations from data analysis informed the re-design of materials, and vice versa. Reflection meetings with teachers, and one reflection discussion with the Boone students (now in 8th grade), continued throughout the data analysis process. In this way the
59
constructs proposed here have been validated through ongoing negotiation of understandings with the other participants in the curriculum enactments.
4) Design rationale of the unit In this section I outline the design goals underlying the curriculum unit itself, with a particular focus on goals for promoting reflection. The unit is entitled “Earth Structures and Processes: Exploring the earth’s crust using models and data.” It was designed by middle-school science teachers Jennifer Mundt, Sonia Flores, Jean Bramlette, Kathleen North-Tomczyk, Thea Raedeke, Jennifer Olson, LouEllen Finn, and Judith Whitcomb, and fellow researchers Ben Loh and Sue Marshall, in collaboration with myself. The design process was iterative, with cycles of writing curriculum, designing materials, enactments in classrooms, reflection and evaluation sessions, and re-design. The complete set of the unit’s lesson plans is attached as Appendix B. This design rationale section is divided into five parts: 1. A discussion of the purpose of a design rationale for this type of research; 2. A brief history of the curriculum design process, overviewing the major iterations of the unit, and the problems and realizations that led to changes made at each step, leading up to the current version of the curriculum; 3. A discussion of the “habits of mind,” or ways of thinking about geological data, that we intended students to acquire through doing the unit’s activities; 4. An overview of two design approaches for the unit, how they were intended to promote reflection, and the rationale for why we expected them to work; and 5. The specific designs of artifacts and lesson structures for four data-rich inquiry activities in the unit, detailing how the designs reflect the pedagogical goal of promoting increasingly reflective patterns of inquiry activity in small groups. This design rationale will be revisited in the Discussion section of this study (6), to examine our design assumptions in light of the data analysis, and to identify design implications of the analysis. 4.1)
Purpose of a design rationale
This design rationale is meant to give background information necessary for understanding the kinds of thinking we intended students to learn and explore. It will help the reader make sense of student discussions in the data analysis. The design intentions described here are the basis for the representation of the data context, as operationalized for this study. 60
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In addition, it is meant to give insights into some of the assumptions that went into this study. In design research we often package our assumptions and our realizations into the things we are designing for the classroom. This design rationale is an attempt to make explicit the assumptions and realizations which are embedded in the curriculum unit. Why is it necessary to make these assumptions explicit? This study does not attempt to figure out how to promote reflection by isolating certain variables and testing them under controlled circumstances, to support or reject specific hypotheses. This approach could be perfectly worthwhile, if we had particular design variables in mind which could realistically be controlled for. But at the time we began this work, our model of reflection in inquiry – and how to promote it – was not at a level of detail or clarity to isolate hypotheses in this way. Instead, we created a curriculum unit, and enacted it in classrooms, using it as a vehicle to develop and test multiple assumptions and hypotheses, in the complex laboratory of daily classroom activity. A strength of this design approach is that we have a more direct translation of our findings to the world of educational practice – laboratory studies sometimes leave us wondering about what we should do with our carefully-controlled findings. Another strength is that we have been able to learn a tremendous amount from our failures and our on-the-fly repairs in the design-redesign process, and have put this learning directly back into the curriculum enactments along the way. However, a weakness of a design research approach is that we run the risk of having no idea of which things mattered for our outcomes, or even a clear picture of what our variables and outcomes were (Brown 1992). By developing and testing hypotheses about teaching and learning within the context of ongoing school activity, we can easily lose track of how our experiences can translate into generalizable understandings. Designed curriculum artifacts are often made from intuition or professional habit, and the underlying assumptions can go unexamined in the research process. Some people dismiss much design research as simply stories of what happened, lacking justification for claims of relevance to other settings. The purpose of this design rationale section is to offset this potential weakness. The intention is to make explicit the assumptions that shaped our design of the Earth Structures and Processes unit. By making these assumptions explicit here, we have better leverage for drawing design implications from our outcomes. Rather than just saying what happened, and then assuming we know what lessons to draw from our story, we can use our design rationale as a point of departure to ask, “How did what happened relate to
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our assumptions about what would happen?” This helps us make a critical appraisal of our design assumptions, adding validity to our design implications, without limiting us to focusing on a few controlled variables. 4.2) Brief design history of the unit The Earth Structures and Processes unit has evolved out of a series of earlier activities designed for different purposes. A brief overview of these activities will help explain the design assumptions embodied in the current version of the curriculum. Summer 1996: A two-day pilot test for the Progress Portfolio
The unit began as a two-day activity for students in a laboratory setting, as a pilot test of an early prototype of the Progress Portfolio, conducted by Ben Loh and myself. We did not have particular learning goals in mind, but rather wanted to see students interacting with a graphical information system (GIS). We wanted to see what kinds of software supports might help them figure out the images in a data visualizer – supports which we would then build into the Progress Portfolio. We assumed that making sense of these images would require reflection, but we didn’t know what that might look like. Three students from a summer “gifted and talented” program volunteered two afternoons with us, in exchange for pizza and a chance to use new computer software. We used the EarthView Explorer software (Columbia University) in tandem with the Progress Portfolio. Teacher instincts told us that we needed to have a discussion about earthquakes before we jumped into the software, so we did the beginning of a traditional “KWL” activity – brainstorming on big paper everything the students knew and wondered about earthquakes. After a remarkably generative 1-hour discussion, we set them up with the computers, and for most of the remaining time they explored whatever struck their fancy. Toward the end of the second session, realizing that we wanted them to talk more about what they were thinking, we asked them to present their “findings” to another graduate student. It became clear that these 6th graders were remarkable students, with huge amounts of prior knowledge about plate tectonics. Their ability to generate interesting “problems” for themselves – e.g. explaining two very deep and big earthquakes off the coast of Spain, in an area where there weren’t many small or shallow earthquakes – was something most students would need lots of support to do.
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Another thing that became clear to us through this experience was that a lot of the reflections students had while looking at the data were grounded in the ideas that had surfaced during the discussion. The “trail of thinking” which was left over after our great discussion – big paper sheets on the walls, with tons of ideas and questions about earthquakes – was very useful for keeping focused on some of the more interesting “problems.” We found that the data representation tools provided in the software – e.g. color-coding plotted earthquakes by magnitude or by depth – seemed to shape the kinds of hypotheses students were generating – e.g. “the deeper ones are bigger.” These representations provided both affordances and constraints on the students’ thinking. We considered how it might have gone differently with other representations available as well. Finally, we sensed the difficulty students had in explaining their thinking about their investigations, due to the lack of artifacts to show what they had been doing. They had used the primitive Progress Portfolio sparingly, and did not have many images with which to “tell their story.” Reflection on their process, it seemed, was hampered by this lack of artifacts. Fall 1996: A written unit plan for a Progress Portfolio project
Ben Loh later wrote out a detailed plan for a plate tectonics inquiry project to be carried out using the Progress Portfolio. This was one of several ideas, from various domains, that we toyed with for a first full-scale curriculum enactment using the Portfolio – though it was never used in this way. The unit plan centered around students mapping the outlines of earth’s plates, using the earthquake data provided in a visualizer like EarthView Explorer (several other software applications were also reviewed). The design had small groups of students each assigned a major city – Sao Paolo, Mogadishu, Honolulu, etc – and taking the responsibility for finding the boundaries of their city’s plate. The Portfolio would be used to collect data supporting the plate boundary predictions – plate boundary lines would be drawn on top of the images in the Portfolio (requiring us to develop some new drawing tools in the software). Students would culminate their investigation by creating a “Plate Hunter’s Guidebook,” explaining to other students how to go about finding plates from earthquake data. The unit plan was written out in some detail. However, for a variety of reasons, we shelved it. For one thing, we felt that there would need to be some big, exciting product
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coming out of the inquiry process, but the artifacts envisioned for the work were all on small computer screens. We never worked out the specific logistics of groups meeting to discuss their boundary lines – how to actually compare their work in the computer. And we were not satisfied that any of the available software applications would give the students the control and ease of data queries that they would need. So the unit plan sat unfinished on the shelf. Fall 1997: From computer screens to big paper maps
A year later a friend and collaborator, middle-school teacher Jennifer Mundt, was chatting with us about frustrations with computer software and curriculum. She was finding that developers were providing glitzy video and graphics, but not the kind of big datasets she wanted for inquiry projects in her classroom. The disconnect between software development and inquiry curriculum was creating a problem for her, right in the middle of a unit on natural disasters! We mentioned to her Ben’s plate-mapping idea, and she took it up right away. However, as she had Windows PC’s in her classroom and the Progress Portfolio was a Macintosh application, we had to leave the Portfolio out of the picture. This turned out to be a blessing in disguise. Jennifer needed a bridge between the activities on natural disasters they had been doing, and this plate mapping task. She started by introducing students to some of the earthquake resources available on the Internet, at the United States Geological Survey site. She set up regions for each group to monitor, and had them download and plot data on a wall map. After some data had accumulated, she led a discussion around this data set, which allowed students to spot the “Ring of Fire” around the Pacific. After contemplating the shortcomings of the computer activity as envisioned up until then, we chose to begin the plate mapping not using software, but using gigantic paper data maps. Ben designed the data map to be 52”x40”, displaying one year’s worth of earthquakes above magnitude 3.0. This map was carefully crafted to be big enough for several groups to work around it at once – affording collaboration and enabling them to see what other groups were doing – and to be so big that the large amount of data would still be hard enough to interpret. At a smaller size, the task would not be problematic at all – students would just connect the dots. Students did the plate-mapping activity using transparency sheets as overlays on the data map. We introduced a “mini-conference” structure for the activity: students from
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different cities met to compare the lines they had drawn, and debate their lines from the evidence. Jennifer used this activity to pursue her ongoing goal of establishing classroom norms in which students debate ideas using evidence, rather than simply arguing from authority. The software was used only after this point – as a way for students to go look for more data on the areas they were unsure about. In this way the students had a need for the data, which had been made problematic by the paper map activity. We used Geodynamics Database software (Johnk and Albertsen 1996), a Windows-platform GIS designed for high school students. Some groups used a round-world projection in the software to question the data patterns at the top and the bottom of the globe. We then had students transfer their plate lines from the flat maps to round globes, using white tape. The activity lasted for 7 days. On the final day, in an attempt to introduce the concept of plate motion, we had students do a clay modeling activity in which they tried to make models of different kinds of plate boundaries – subduction zones, rift zones – from twodimensional pictures. In a final discussion around the finished world plate map, we tried to explain how data could show them the directions plates were moving in, by identifying subduction zones. Students did a magnificent job of mapping their plates, and debating their lines from the earthquake evidence in the “mini-conferences.” However, many students had trouble saying just what a “plate” was; and the modeling activity and discussion of plate motion were completely baffling for them. While they had learned a tremendous amount about making predictions from data, and debating using evidence, many of the underlying earth-science concepts were still sketchy for many of them. What we learned from this activity was: 1. The investigation with big data maps was engaging, and the mini-conferences could promote debate of interpretations using data as evidence; 6. The activity needed more grounding in the underlying science concepts – plates, crust, boundary zones – in order for students to connect the data activity to explanatory models of the earth; 7. Multiple representations of earth and the earthquake data were difficult for students to manage (e.g. going from paper maps to computers and back), but they seem important for putting together connected understandings;
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We also learned a valuable lesson about curriculum and software: sometimes the best thing to do is leave out the computer altogether! This was a clear case where the technology did not easily serve the overarching learning goals. But students did not get a chance to benefit from the main power of the computer database, which is using data to characterize the complex data patterns from which to determine boundary zones. Winter-Spring 1998: Experimenting with modeling and staging activities
The chance to pursue the design of the unit further came later that school year. The Center for Learning Technologies in Urban Schools (LeTUS) provided a context at Northwestern University in which we could take the “seed idea” of the unit as we had done it, and bring it to new teachers to develop it further. This was the purpose of the Center’s “work circles,” which started in February 1998. I took the lesson plans and materials from the Boone 1997 enactment and brought them to teachers at elementary schools in Chicago’s Region 4: Jean Bramlette from Haines Elementary School, and Sonia Flores and Kathleen North-Tomczyk from Saucedo Academy. We formed a work circle, met on a weekly basis to design a unit around these seed activities, and began piloting activities with students at these schools. Many of these activities were staging activities to lay the earth science groundwork for the plate-mapping data activity. With students at both schools, we tried out modeling activities to explore topographic mapping, latitude and longitude, and variations on the activity of plotting earthquakes by regions. We found that the plate mapping activity – with paper maps and with the GIS software – was one that required skillful facilitation. Students were likely to connect the dots and be happy to be done – being asked to go back and justify their lines was not something many of them “bought into.” These activities needed to be tied into (1) the regular norms and expectations of the classroom, and (2) a coherent trajectory of exploration within the unit itself. Many suggestions for facilitating this activity, as well as the discussions before and after, were developed in the context of trying to replicate Ms. Mundt-Leimberer’s success with this activity in other settings. We also learned that the modeling activities we were developing were not connecting with the other parts of the unit. Students did not see the connections between their models and their plates – the connection was implicit if you understood the domain, but was not explicit in a way that would help them understand the domain! In fact, the staging activities that we explored often seemed to detract from the inquiry goals,
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focusing students on surface features and taking up time. Modeling activities were clearly needed, if only as a means of translating one representation into another – but they needed to be better connected to the flow of the data inquiry. Summer1998: Creating a coherent series of staging and inquiry activities
These realizations fed directly into the re-design process that came next. Ms. MundtLeimberer and I collaborated over the summer of 1998 to take the ideas that had been tried over the previous year, and create a coherent inquiry unit. We re-designed the staging activities to introduce a dozen real structures on the earth’s crust – the Himalayas, the African Rift Valley, the Hawaiian Islands, etc. These “case studies” at the beginning of the unit were meant to ground students in thinking about real places on earth, and connect the plates activities with topographic structures at the very outset. They were followed up by student dramatizations of myths and legends explaining the formation of real earth structures, to introduce the idea of explaining the formation of earth structures. Clay modeling activities were redesigned to be topographic models of real places on earth (Japan, Iceland) – not abstract domain concepts (like “subduction zone,” as in Fall 1997), and not generic formations (like “a steep mountain,” as in Fall 1998). An additional modeling activity was added, in which students use their final plate boundary predictions as the basis for making clay models of their plates. The intention here was to help students visualize their data-based predictions in three dimensions, and to provide a medium in which the earth structures from the beginning of the unit could be represented on the plates. The plate mapping activity was written up, with suggestions on how to facilitate discussions during the “mini-conferences” to promote debate using data as evidence. Activities were written up in which students use data to identify different kinds of boundary zones – an idea that had not been tried yet. All unit lessons and materials were put into one curriculum binder, and the LeTUS Center held a “kick-off” workshop in which we demonstrated to the attending teachers the ideas underlying the main unit activities. We explained the rationale for the staging activities and the activities with large datasets, and we gave a tutorial in using the software. During the following school year the unit was enacted by 10 teachers in Chicago, Indiana, and California (mainly teachers who had attended the workshop). The
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classrooms in this study are three of them. The Progress Portfolio was used to support the unit in one classroom – Jennifer Mundt’s, the primary focus classroom for this study. At the end of the school we held a meeting with teachers to revise the curriculum, based on their experiences teaching it. We found that many aspects of the unit’s design were helpful to teachers in promoting reflection around complex data. The flow of unit activities created some opportunities for productive reflection, but in other cases did not tie concept-building activities into data-analysis activities. Some teachers spent lots of time on the engaging and interesting staging activities, then ended up short-changing or leaving out some of the inquiry activities with data. Teachers found that, during plate mapping, students often reflected back to some of the information learned about the earth structures in the “earth structure expert groups” activity, but rarely to the clay topographic models they had made. Transitions from one activity to another – the crucial changes that make a unit “flow” or not – were difficult for many, and the sense of a unified whole was still incomplete. Next steps: Re-design of the unit
This brief history provides the background for the design approaches embodied in the current unit, as detailed below in section 4.5. Since the enactments studied for this dissertation, we have re-designed the unit, revisiting many of the design assumptions in light of teachers’ and students’ experiences in the previous enactments. Some of the changes made in this re-design are described in Section 6, as we revisit our design rationale in light of the present data analysis. 4.3) Ways of thinking about geological data The Earth Structures and Processes unit was intended to introduce students to the domain of geophysics. Every domain of inquiry has its own rules, or “ways of seeing,” which determine what constitutes a good or valid question, observation, or explanation. These rules are determined by the characteristic habits of mind associated with inquiry in that domain, as well as by the kinds of data used in the domain. In this study, I explore the use of datasets in the domain of geophysics. This domain is chosen for a number of reasons. First, it is a domain in which complex data are often represented on geographic maps (along with other domains such as history, sociology, paleontology, etc). The growth in mapping and GIS technologies in recent years makes the study of map-based datasets important in itself, and the field of school-accessible GIS software is rapidly growing. It
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is valuable to understand how these map-based data representations can be used to promote learning. Second, phenomena associated with plate tectonics (earthquakes, volcanic eruptions, mountain building, “continental drift,” etc) are subjects which are represented in core middle school curricula and standards (CPS 1997), and which are also often interesting to students. These factors make this domain a worthwhile one for developing curriculum which is likely to be valuable to schools, and which is likely to be used. They have contributed to a high level of interest in enacting the unit, on the part of middle school teachers we have contacted so far. Third, geological inquiry is an observational science -- one based on drawing conclusions from observation of existing phenomena in the world, rather than from laboratory experimentation or other manipulation of variables to observe change. There is a larger body of research on student thinking and learning in scientific domains associated with experimentation (e.g. Klahr, Dunbar et al. 1990; Schauble, Glaser et al. 1991; Schauble, Glaser et al. 1995) than in the observational sciences (e.g. Smith 1996; Tabak, Smith et al. 1996). Thus exploring the kinds of cognitive processes and activity associated with reflective inquiry in an observational science domain is valuable to the research community. A “way of seeing”: visualizing earth’s crust as structures and processes
Studying the structures and processes of earth’s crust requires imaginative visualization. The actual structures being studied are often too large, inaccessible, or otherwise unobservable. While students may find it easy to imagine a mountain, an island, or even a continent or ocean, their conceptions of such structures are often incomplete. How tall is a “big” mountain? What might the ocean floor be shaped like? Images such as sea level, craters atop mountains, and ocean-floor trenches are essential for studying the earth’s crust, and we have found that they are often difficult for middle-school students to visualize. Also, there are structures which are not directly observable which are central to this domain, such as crustal plates and boundary zones. These structures require that students develop altogether new ways of visualizing the earth’s crust. In addition to visualizing structures which are not directly observable, this domain also requires visualizing processes of change affecting these seemingly-unchanging structures. Students often have some conception of the processes of volcanic eruption and earthquakes, two processes which can be visible to the eye. However, their imaginings of these processes are usually full of misconceptions (Gobert and Clement 1999), such as
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the belief that the earth “opens up” during an earthquake, or that volcanoes are caused by hot weather. Beyond visualizing these more observable processes, the domain requires one to visualize processes that take place over large periods of geologic time, and have no ready metaphors in students’ life experiences. These include the motion of crustal plates across the spherical surface of the earth, such that continents and oceans change shape and position with respect to one another. Also, the image of a plate in motion requires the concept of a structure which is simultaneously destroyed at some boundaries, and added to along other boundaries. It is a process of continuous but invisible change. These kinds of visualizing are some of the essential habits of mind associated with this domain. A geologist must be able to observe and identify a mountain range, visualize it as a structure which is related to the topography around it, and imagine a series of both slow and rapid change processes which may explain its existence: the motion of one plate toward another, with progressive subduction of a segment of oceanic crust underneath a segment of continental crust. These visualizing habits are intricately connected to representations of data used in the domain. Geological datasets
The domain of plate tectonic studies involves several types of data, which are represented in many different ways for different purposes. Every dataset has many assumptions about prior knowledge designed into it, both in its content and its representational scheme. The words, numbers, and conventions used are based upon assumptions about what the user can interpret. Also, datasets are usually created for certain inquiry purposes, to represent information obtained from a particular set of queries about the world. Thus every dataset has different affordances for inquiry. In this study I focus on a number of different datasets associated with this earth science inquiry domain. These include: •
tables of numbers representing earthquake locations, times, depths and magnitudes;
•
topographic and relief maps of particular earth structures;
•
printed data maps displaying earthquake locations; and
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•
a GIS software application, Geodynamics Database, which enables students to display a range of earthquake, volcano, and topographic datasets on an interactive world map interface.
In order to make relevant observations from the first type of dataset, a tabular list of earthquake events, one must be able to imagine the latitude and longitude values as a location on the earth; decode the time values to idenitfy events that might be related to each other; and interpret the depth and magnitude values in order to characterize each event in terms of the others (bigger and smaller earthquakes, etc). Making meaning of topographic and photographic representations of places on earth requires ignoring irrelevant detail (e.g. ground cover, small irregularities) and focusing on characteristics which might be related to tectonic motion (sudden steep changes in elevation, as compared to gradual changes). Satellite photographs and topographic mapping software often provide data which focuses the knowledgeable observer on these relevant details. The geographical representations of earthquake and volcano data require visually identifying patterns in point data -- differences in the concentration of points in different areas. These observations must then be connected to assumptions underlying domain thinking and be communicated understandably with teacher and peers. Prior knowledge of domain concepts
In order to make meaning of such datasets in the service of inquiry, inquirers must have an understanding of the theoretical underpinnings of the domain. The currently-held scientific beliefs about the domain are not self-evident in the data, but rather are shared through communications among practitioners. Scientists build their work around a collection of commonly-held explanations which shape their data interpretations, such as the belief that earthquakes occur at boundaries between plates; that continental and oceanic surfaces often share common plates and move in tandem; etc. It is not only the ability to explain these beliefs that is necessary for inquiry in the domain. Inquirers must apply relevant domain explanations to relevant data observations. For example, scientists believe that volcanoes are frequent close to the edge of the upper plate at a subduction zone. This belief is only useful in inquiry if a student can identify a pattern of volcanic activity alongside a line of earthquake activity, identify the earthquakes as the likely plate boundary, idenitfy the volcanoes as the result
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of subduction, and then predict plate motion of the two plates using the information that the volcanoes are on the top plate. Thus prior knowledge in the domain is characterized by the flexible application of that knowledge in the service of generating explanations for observations from data, explanations which coincide with the commonly-held beliefs of the scientific community. 4.4) Two design approaches based on a trajectory of artifacts Over the iterations of this unit, we (the designers) have developed a series of instructional goals to promote a trajectory of change which we hope students will progress along over the course of the unit. The end goal is for students to be able to use the kinds of datasets and domain concepts outlined above, to conduct reflective inquiry into the structures and change processes of the earth’s crust. How do the designed curriculum artifacts embody these instructional goals? To present this design rationale, we begin with two overarching design approaches. These approaches are: 1. Students create interpretive models from complex datasets, and then use these models for later investigation, in iterative cycles 2. Students construct a narrative of the inquiry using a “trail” of their designed artifacts I will first provide a brief explanation of each approach, with an overview of how the design approach is intended to shape activity. This includes our assumptions about how artifacts would shape reflection, and a justification of why we believed the approach might be successful. Then, in the following part of this section (4.5), I will outline in more detail how these two design approaches are embodied in the specific design of four main curriculum activities from the unit. These are the four Focus Activities that structure the data analysis in Section 5 – the three “inquiry cycles” with increasingly-complex sets of data (design approach 1), and the “presentation preparation” phase (design approach 2). Design Approach 1: Designing models from data iteratively
We want to strike a balance between having students interpret complex data representations, and having students generate artifacts that promote reflection. In the unit lesson plans, we have designed a series of inquiry cycles in which students use one representation of data (a large dataset in one medium) as the basis for creating a new
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representation of data (a model embodying their interpretation of the dataset, in another medium). Unlike demonstration models that are not based on data, these artifacts embody students’ detailed interpretations of complex datasets at each step. There is no conceptual distinction between a dataset and a model representing data – there is no such thing as “raw data.” Every dataset is a designed artifact itself, a model embodying the designer’s assumptions and decisions. Each model created by students in one phase of activity embodies their interpretations of the complex dataset(s) used in making it. These models are subsequently used as data sources, in addition to new and more complex datasets, for developing new interpretive models in the next phase of activity. This is one of the design approaches used repeatedly in the unit: interpret a dataset à create a model à use the model as a dataset à create a new model. New, increasingly complex datasets are introduced into the inquiry along the way, affording the creation of successive models that are increasingly rich with data and concepts. Artifacts made by students play two roles in activity – first “the redesigned,” and then “available designs” (New London Group 1996). This design approach (represented in Figure 4.1) is intended to prompt reflection in two ways: during the process of creating a model from data, and subsequently in the use of that model as a product. The act of making a model from a dataset may prompt a certain degree of engagement with that dataset – depending of course upon students’ conceptions of the task, norms of class and group participation, etc. Whatever engagement with the complex data happens at this point has the potential to prompt reflection, to afford the act of making the data problematic. But then returning to that model at a later point in time, to make something else (a prediction, another model, an explanation), has the potential to prompt a new round of reflective engagement.
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Data used by students
Product STUDENTS CREATE DATASET
STUDENTS MODEL PLATES FROM DATA
STUDENTS MODEL STRUCTURES
Figure 4.1. Design Approach 1: Designing models from data iteratively
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Design Approach 2: Using a “trail” of designed artifacts to teach other students
In addition to using previously-designed artifacts for interpreting complex data, students also use them as “props” for explaining their understandings to other students. This design approach is used in the “presentation preparation” and “final presentation” phases of the unit, and in smaller ways in minor presentations between groups as culminators of each staging activity and inquiry cycle. This kind of teaching task has been explored by many teachers and researchers as a valuable lesson structure (Johnson and Johnson 1982; Palincsar and Brown 1984; Kagan 1992; Brown and Campione 1994). The rationale is that needing to explain to an audience can prompt students to make their understandings explicit, and this need can make their understandings problematic for them, prompting reflection. The specific approach we take here to this lesson structure is what we have called the “trail of artifacts” approach. The presence of numerous artifacts from different points in time is intended to aid in reflection as students prepare their final presentations. By having students create new artifacts from complex data at intervals throughout the unit, we intend to “seed” the classroom environment with many “snapshots” of interpretations and understandings from different points in time. These artifacts can be useful for students in preparing to teach others – they have value for explaining visually, for establishing intersubjectivity with other students. But they also constitute a de facto “trace” of actions taken and decisions made over the course of the inquiry. This design approach is represented graphically in Figure 4.2. This idea of recording a trace of inquiry decisions, to serve as a prompt for reflection, has been pursued in several software environments (Collins and Brown 1988; Shute and Glaser 1990; Schauble, Raghavan et al. 1993; Loh, Radinsky et al. 1997). This curriculum unit’s design is an attempt to use a similar approach with artifacts in the physical environment, in addition to “virtual” artifacts in the computer. By constructing a narrative – a story of their project – around these artifacts that are rich in data interpretations, students have opportunities to reconsider their understandings from a new, removed perspective – i.e. opportunities to reflect on their learning.
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Figure 4.2. Design Approach 2: Using a “trail” of designed artifacts to teach other students
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In the theoretical framework section above we discussed the concept of the “flow” of classroom activity over time, and the significant role of artifacts in mediating this flow. Curriculum designs often embody a very intentional flow, or trajectory of experiences for students. However, the internal logic of this trajectory can easily be lost on students, who may perceive events as simply happening when they do, for no apparent reason. Part of the intention of having students use artifacts from different points in time to construct a coherent narrative is to prompt them to notice and reflect upon the flow of activity which has taken them through the unit. These two approaches are not the only ones underlying the curriculum designs. They also were not explicit approaches at the outset of our design process. Instead, they emerged over time as we (the various designers) made changes to the unit at each iteration. However, in the most recent re-design discussions with teachers, the concepts of flow and iterative usefulness of artifacts became very explicit in discussions. These two design approaches are embodied to an even greater extent in the most recent redesign of the unit, based on observations and suggestions of teachers. In the next section we examine how these approaches are embodied in four phases of the unit, the four inquiry cycles which are the focus activities for this study: Focus activity 1: Plotting current earthquakes Focus activity 2: Mapping earth’s plates Focus activity 3: Identifying plate boundaries and motion Focus activity 4: Presentation preparation These four focus activities embody the two design approaches discussed above, as represented graphically in Figure 4.1. These four are not the only activities that embody these design approaches – for example, the artifacts creating during the staging activities of the unit are used as sources of data for later inquiry. But these four are chosen to organize this discussion and the data analysis, as they are the activities in which students must make sense of complex datasets. As such, they are of most interest for the present study. 4.5) Pedagogical goals of four Focus Activities First I provide an overview of the progression of the unit as a whole, to show how the focus activities fit into the bigger picture. Then each focus activity is described in terms of the artifacts used by students (“available designs”); the lesson structures constraining
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the way those artifacts are to be used; the rationale for these designs based on our model of reflection; and finally, the artifacts produced by students in each activity (“the redesigned”). Overview of the unit
The Earth Structures and Processes unit interleaves computer activities, using data visualization software and Internet-based datasets, with a wide range of other classroom activities, addressing concepts and skills related to geology, geography and plate tectonics. The unit consists of three main phases: Staging activities, Inquiry cycles, and Presentation activities (see Table 2). Each phase is divided into separate lessons intended to help teachers build a progression of ideas into whole-class discussions and small-group work. The intent was to provide teachers with a variety of “staging” activities to suggest the kinds of observations, questions, and explanations which we thought would be most fruitful in later work with the complex datasets used in the “inquiry cycles” (our four Focus Activities).
Table 2: The Earth Structures and Processes unit. Data-rich investigations are highlighted.
Unit activity
# of lessons 1
Top 10 Earth Structures
2
Myth Readings
2
Clay Earth Structure Models
2
Plot Current
3
Earthquakes
3
Clay Plate Models
1
Plate Boundaries Mini-lesson
1
Identify
Zones
3
Preparation
2
Boundary
Presentation
Final presentations
1
PRESENT
Plate Mapping
CYCLES
1
INQUIRY
Earthquakes Mini-lesson
STAGING ACTIVITIES
Intro & Crust Drawing
Focus Activities for this study
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The staging activities are skill-building and concept-building lessons, in which students do mini-investigations of particular structures on the earth; create models of earth structures from topographical maps; and study and enact myths as explanations of earth structures. Map-making, plotting, and map usage teach concepts of graphic representations of data, for both continuous values (elevation) and point data (earthquake magnitude and depth). These staging activities introduce domain concepts both from the abstract and from the particular. They also provide artifacts which are meant to be revisited later in the unit: clay models of earth structures, reports on earth structures, “stagebills” containing mythological explanations of earth structures. The staging activities may come before, or be interspersed with, the four inquiry cycles involving analysis of complex datasets. These four are key activities for careful analysis here because they are the parts of the unit in which students are working with large sets of data. The other activities (reading, modeling, presenting, etc) are equally important and challenging, but do not require students to make meaning of complex datasets. The first inquiry cycle involves gathering current earthquake data from the Internet and plotting it on a world map, to observe locations and measurements of tectonic activity and generate questions. In the second inquiry cycle students use a full year's earthquake data set to predict plate boundaries around the globe; students use a transparency overlay to draw their predictions, and use a “jigsaw” lesson structure and additional data to check their predictions. The third inquiry cycle uses the discovered plate boundaries, along with volcano and topographic data, to predict directions of plate motion; students create clay models representing plates, prominent earth structures, and plate motion. The complex data visualizations available in the Geodynamics Database software are used during the last two inquiry cycles. These investigations are interspersed with lectures and readings in preparation for the investigations; whole class and small group discussion activities to explore concepts and understandings; and hands-on activities to build plotting and modeling skills. Each of the four focus activities involves the analysis of different sets of data, and results in different products of student work. The four focus activities are inter-connected through the artifacts used and created by students. Focus activity 1: Plotting current earthquakes
After a whole-class brainstorm discussion about the causes and locations of earthquakes, students plot the 20 largest recent earthquakes from around the world. This is extended
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by dividing up the world into regions; groups monitor and plot earthquake activity in their region for a period of time. Once each group has plotted a set of earthquakes from their region, all groups’ data are compiled on one wall map. In this way a large dataset is assembled by the class as a whole, which is then studied for patterns in the data. Students make use of the artifacts created during the staging activities – reports about various earth structures, topographic models of certain of these structures – to help them make initial predictions of where in the world they think earthquakes might happen. Then they are given materials for the main activity – lists of recent earthquake events downloaded from the USGS web site, organized by region; one class wall map for compiling all groups’ plotted data; and colored stickers for representing earthquakes. This part of the unit was designed to give students an immersion experience in information about where earthquakes happen. The idea was that this immersion would problematize their prior assumptions about earthquakes, and would also problematize the many lists of numbers and dots-on-maps which they were to work with. By bringing out their prior assumptions in a brainstorm, and then immediately making observations from lots of data, we hoped to stimulate reflection on both the assumptions and the data. Another goal of this activity was to give students experience in generating a set of data for themselves, by choosing information from one medium (printouts of text), and representing it in another medium (dots on maps). We hoped to counteract the idea that datasets are somehow handed down divinely from the Gods of Science, to demonstrate given facts – we wanted them to problematize where sets of data come from, by creating some themselves. We wanted them to learn to be careful and exact in reading and plotting data; to develop their skills for reading latitude, longitude, and other information in text and on maps; and to become familiar with world geography for the purpose of finding exact locations. We wanted them to learn to use different pieces of information to cross-check their plotted data for accuracy. We wanted them to have the chance to look for emerging patterns in a dataset as they created it, to give them a feeling for how data can be gathered intentionally, over time, to further one’s understandings. We wanted them to learn to tie their questions from class discussions to their work with data – by comparing their prior assumptions with emerging data patterns, and by generating new questions for discussion from the emerging data patterns. We wanted them to learn to think of data in terms of patterns which must be interpreted, rather than as clear answers to simple questions.
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We also wanted them to learn the limitations of particular datasets for pursuing research questions. We hoped that the limitations of their plotted earthquake data would create the need for more data to satisfy their curiosity. We wanted them to learn about where earthquakes can happen, to wonder about why, and to want more data – so that they would be primed to study the larger, more complex sets of data to follow in the unit. Finally, we hoped that assigning groups to a specific region for data gathering would build their attachment to the activity and the datasets, by providing a “geographic identity” for their group. The final product of students’ work in this activity is a class wall map, with large numbers of stickers on it representing plotted earthquakes. The activity was intended to accumulate enough data to suggest possible patterns – most likely a ring of earthquakes around the Pacific Ocean – without making these patterns completely evident. The lesson plans suggest a question for discussion around this artifact: “What do you think this map would look like if we did this for a year?” In this sense, the final artifact was meant to problematize earthquakes as data points, suggesting the possibility of a pattern, such that the pattern might be made problematic in the next phase of inquiry. Focus activity 2: Mapping the earth’s plates
As noted above, the wall map from Focus Activity 1 was intended to be used as a starting point for problematizing larger patterns of data. The next source of data was a large paper data map with dots representing all large earthquakes recorded worldwide over the course of one year. The tools for analyzing this map were plastic overlay sheets, on which to draw predictions of plate boundary outlines, and markers of two different colors, to differentiate between “Sure” and “Not sure” boundary predictions. At the end of this activity an addition resource is added: the interactive earthquake database in the GIS computer software. In “mini-conference” presentations, groups compare their interpretations and findings with those of other groups, and identify areas that need more work. The miniconferences provide a chance to promote and sustain debate using data. Debates were seeded by referring back to students’ successive predictions of plate shapes, made at various points in time. This is meant to highlight the tentative nature of their predictions and suggest the value of data in improving them, rather than focusing just on right and wrong answers. These presentations lead to further investigations with data, as groups’ questions become more focused and refined around needing to understand particular phenomena.
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The final product of this activity is a world map of the plates created by the students, drawn on taped-together plastic overlay sheets. This artifact represents a culmination of two phases of inquiry on patterns of earthquakes, and can be compared with various “official” world maps of plates created by scientists. Students write their plates’ given names on this map, making it their own. This artifact thus represents both a culmination, and also a starting point for further investigation in Focus Activity 3. Focus activity 3: Identifying boundary zones
After using one large dataset for making concrete predictions, students are taught how to query much larger, interactive data sources. Students use Geodynamics Database software and other data sources to refine all groups’ predictions of plate boundaries, investigating the areas that were argued over in the previous phase of inquiry, and areas where predictions were less certain. Models and images showing students’ plate boundary predictions are used to generate new questions about the directions of plate motion, requiring further data and another inquiry cycle. The class’ world plate map is used as a resource for groups to create smaller clay models of their plates, representing topographic structures (building also on earlier topographic models, though they are not explicitly linked). These models are used as materials on which to predict the motion of plates at their different boundaries – they contain in them the accumulated interpretation of data from Focus Activities 1 and 2, as well as additional topographic data. Students now use the full datasets provided by the GIS software: various earhtquake, volcano, and topographic datasets. In addition, the curriculum materials include “information sheets” describing data patterns at different kinds of boundary zones, for students to use as reference materials in their investigations. These materials provide access to the kinds of domain concepts needed to determine plate motion and direction; they can be referred to by students as needed during their investigation. This is the part of the inquiry we have been trying to prepare them for, when they are given access to large amounts of data in an interactive medium. They have been through a series of experiences to put some of the “data context” pieces in place, and now have an opportunity to reflect upon them in making sense of the data in the interactive computer database. The final products of work in this phase include the clay plate models, with boundaries and plate direction inscribed on them, and the class plate map, with the same information
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inscribed for the whole world. These artifacts are used to seed discussion of “What we now know” and “What we still don’t know.” The refined predictions students can make around these artifacts can generate new, more sophisticated directions for students’ investigations. Focus activity 4: Preparing a presentation of the inquiry
Students create presentations and other instructional activities for a younger class, using the artifacts created in the unit to explain their understandings of earth structures and processes, and also summarizing their inquiry activities to show how they developed these understandings. They are asked to explain their own learning process, as well as the domain concepts they have come to understand. In this activity students are to make use of all of the artifacts they have produced in the unit. By revisiting all of their “work products now as raw materials for the next phase of work, the intention is that students will have to look for the understandings and data which are inscribed into these artifacts, to make sense of them anew. By having students create a coherent “story of a plate,” we intended that they revisit their earlier understandings and assumptions, and solidify their new understandings. The “trail of artifacts” that they have created was intended to seed their reflections here. By having students present to other students, both about the concepts and about their process, we hoped to motivate them to strive for clarity, and the need for honing their own understandings. The audience for their inquiry narratives was meant to motivate clarity, detail, and explicitness – which would hopefully prompt new reflections on the data context relationships as well. Revisiting the artifacts in this teaching context was meant to prompt them to revisit their own udnerstandings. The final products of this presentation activity are: (1) a script for the presentation, which puts a “plot” into the story of what they did, and which makes their changing understandings explicit; and (2) a coherent “exhibit,” or ordered collection of their artifacts, to represent the flow of their inquiry narrative. Summary: the intended trajectory as embodied in curriculum artifacts
Taken together, these four Focus Activities are based on the two design principles outlined above: the iterative revision of models representing data and concepts, and the development of a “trail of artifacts” documenting the history of the investigation. The design of the unit so that students’ work products are used again for later analysis is an
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attempt to make it likely that assumptions will be revisited. This approach is meant to provide motivation for iteration and improvement without just making them “do it again.” The trail of artifacts created during the unit provides a “trace” for students to use in recreating their thinking for a final presentation. The artifacts are intended to make it more likely that students will tell the story of their evolving understanding, rather than just reporting facts to other students from a position of authority. The trace affords a more thinking-oriented presentation.
5) Data analysis: reflection in classroom enactments In the theoretical framework above, we have examined what reflection in inquiry is; the contexts in which it can shape learning; and why it is important for making sense of complex data. In the design rationale section, we have discussed how we intended the designed artifacts of the curriculum to afford and promote reflection during inquiry activity. In this section we examine the kinds of reflective episodes that took place in the course of enacting the Earth Structures unit, relating them back to the theoretical framework and the design rationale. This section is divided into four parts. The first part (5.1) provides some prototypical examples of reflective episodes in work with data, to give a sense of the kinds of talkaround-data that occurred in the classrooms. The theoretical models of the three contexts for reflection are used as organizers for connecting these episodes back to the framework. The prototypical examples in this first section are not connected with the question of student learning, but rather serve as exemplars to introduce the use of the framework for characterizing reflection. The second and third parts of this section (5.2 and 5.3) are case studies of two small groups within the focus table-group in the Boone classroom. These case studies connect individual episodes of reflection with larger patterns of student learning. The case studies are designed to show the relationships among change in the three contexts: •
changing patterns of activity in the task context (guided participation in smallgroup interactions with complex datasets);
•
students’ development of reflective dispositions toward complex data over time in the role context (learning as participatory appropriation of roles); and
•
students’ development of conceptual understanding in the data context (apprenticeship to geo-scientific habits of mind, as represented in the curriculum design rationale).
The fourth part of this section (5.4) is a discussion of the implications of the case studies for understanding reflection in inquiry more broadly. Comparison groups from other classrooms are used to examine the generality of the observed patterns of learning from a broader perspective.
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5.1) Prototypical examples: What did reflection look like? Before we begin to examine patterns of activity and learning for particular students, we need an overview of the kinds of reflective episodes that occurred during the unit. To begin we examine three prototypical episodes of student reflection in small group work with data. The purpose of these three prototypical episodes is to serve as exemplars of the kinds of interactions we will be examining in greater depth within the case studies. The graphic representations of the three contexts for reflection (data, task and role) are used throughout this data analysis to represent the relationships being uncovered in the discussion. Each context is shown as a circle with its constituent elements on it. To keep these representations from being too disruptive, I have abbreviated them – each context is identified by an icon, and each element is identified by its initials (see Table 3). Table 3: Representation of activity contexts for the data analysis
Data Context
Task Context
Elements RW =
real-world items
DI
=
individual data items
DP
=
data patterns or relationships
M
=
models (from concepts or data)
DC
=
domain concepts
Elements CT
=
student conception of task
AD
=
action decisions
TG
=
teacher guidance
GN
=
group norms of interaction
A
=
artifacts: materials and tools
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Role Context
Elements SI
=
student identities
B,U =
student beliefs, understandings
PE
=
prior experiences
CN
=
concept’ns of classroom norms
SR
=
student role in activity
When an instance of problematizing an element is identified in discourse (explicit questioning or wonderment, as described above), the element is circled in the graphic. When an explicit or implicit connection between elements is suggested in discourse (i.e. a verbal “reminding”), they are connected by an arrow (see Figure 5.1).
Figure 5.1. Example representation of a reflective comment problematizing a data pattern, and connecting it with a domain concept.
These graphic representations are intended to keep the discussion grounded in the theoretical framework, and to bridge between the curriculum design rationale and student discourse. The prototypical episodes below illustrate this representation scheme. (All student names throughout the data analysis are pseudonyms.) Episode 1 (from Focus activity 1 – Plotting earthquakes)
In the first example, a group of students has just received a list of recent earthquakes in their assigned region, the Central USA, which they are to plot with stickers on a world map. The beginning of this excerpt marks the first talk at the table about this task. Joel:
[looking at the list he has just been handed] ‘96. the latest is right here [pointing]
And
88 Mario:
Oh my god! [pointing at the list] … All that is in 2 years. All that is in 2 years!
Marie:
That is pathetic! Wait, when’s a recent one? over to look at the list]
[leaning
… Mario:
August 23rd!
Marie:
[wrinkles her brow] Is that in Kentucky or something? Cause there was a big one in Kentucky
… Joel:
The biggest was 4.3!
Mario:
But when they come, they come big!
In this example, these three students are generating observations, questions, and explanations for the data set they have been given – not as part of the assigned task to plot them, but as characterizations of the data from a range of other perspectives. These are examples of problematizing the data. Joel notices the “date” column showing when they happened (“’96”) and looks through the list for the latest earthquake (“And the latest is right here”). He also finds the one with the biggest magnitude on their list (“The biggest was 4.3!”). These unprompted characterizations of data points, specifying their relationship to the set as a whole, show Joel’s attempt to impose meaning on the big page of text in front of him. He is problematizing data points (DI), examining them in the context of their relationship to the dataset as a whole (DP), as illustrated in Figure 5.2.
Figure 5.2. Joel problematizes data items by comparing their values with the set as a whole.
Mario expresses amazement at the amount of data – total number of earthquakes – for their region over two years’ time (“All that is in 2 years!”). His amazement at the amount of data over two years’ time shows that he is translating data values (dates for each quake) into their real-world referents for the dataset (span of time). He later combines Joel’s observation of a 4.3 earthquake with Marie’s characterization of their region as
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“pathetic” (i.e. for having so few earthquakes), and generalizes a rule about the region: “But when they come, they come big!” He has problematized the relationships among data values (number of data points by range of date values), considering one data point in relation to the set (the 4.3 earthquake), and making both explicit (span of time) and implicit (characterization of region) connections with real-world referents of the data (Figure 5.3).
Figure 5.3. Mario problematizes data patterns, relating them to point values and real-world referents.
Marie asks for a recent date-value data point (“Wait, when’s a recent one?”), connecting it with her memory of a recent news item she has heard (“Is that in Kentucky or something? Cause there was a big one in Kentucky”). She has problematized a data point, being reminded of a prior experience (hearing news) involving real-world referents of the data (an earthquake in Kentucky). Marie has made a reflective connection both inside and outside of the data context, as represented in Figure 5.4.
Figure 5.4. Marie relates data to real-world referents, and also to a prior experience of hers.
In problematizing the data set for themselves, these students actively seek connections to meanings beyond the immediate plotting task: data points that have special status in the set, prior experiences that might relate to the data, and a characterization of earthquake activity in the region based on connecting these observations. These active attempts to make meaning of complexity are prototypical examples of reflection in data-rich inquiry.
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Episode 2 (from Focus activity 1 – Plotting earthquakes)
In another classroom doing the same activity (plotting earthquakes), we can see examples of reflection that problematize the inquiry situation in different ways. Magalys and Dalia have been plotting several data points with stickers, each one finding a latitude or longitude value, then tracing the lines together to meet at the earthquake location. The numbers they are calling out are the longitude numbers along the top of the map, as they move a finger along. Magalys:
135, 136. Got it? OK, move it. [they move fingers slowly towards middle] Right here. What’s it called? [looks at list for place]
Dalia:
There’s not even any land right there. be right here on this little thing
Magalys:
It has to be in Alaska – we did it wrong. Look for 58 over there – and 136 – 136 would be right here
It has to
[they trace their fingers again, come to same spot] Dalia:
I think we’ve been doing it really wrong.
Here the students do not set out at first to problematize aspects of the situation, as the students did in Episode 1 above. But as they go along following the directions, they encounter something that prompts them to do so. When they find their earthquake location, they notice that “There’s not even any land right there” – making an explicit connection between the point on the map (DI) and the place in the world that it represents (RW). This presents an anomaly for them: they believe earthquakes can only happen on land. We can tell this by the fact that Dalia doubts the accuracy of the location. This is an act of problematizing. It is easy to imagine students finding the same spot and simply sticking their sticker down there, following the instructions, without thinking about whether it’s on land, or even thinking about the fact that it is supposed to be an earthquake. Nothing inherent in the materials or the instructions forces them to pull back and question their spot because it is not on land. To generate this “perplexity” for themselves in this situation, Dalia has problematized the data point, making an implicit assumption that the earthquake has to be on land, and looking for nearby land (“It has to be right here on this little thing”). Magalys makes a further connection to make sense of this confusing situation, looking back at their list to check where in the world their region is: Alaska. This is a reconsideration of her conception of the task (CT), i.e. we’re plotting earthquakes in
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ALASKA. She uses this perspective to question their strategy for completing the task (AD): “We did it wrong.” Dalia double-checks their plotting strategy, landing again on the same spot in the ocean, and then steps further back from the immediate task of putting stickers on the map, to question their whole approach: “I think we’ve been doing it really wrong.” These active attempts to make sense of a problem are represented in Figure 5.5.
Figure 5.5. Magalys and Dalia’s reflective consideration of a confusing data point.
These students, like the students in the first example, are generating questions, observations, and explanations to make meaning of the data. However, instead of problematizing elements of the data context on their own, they are prompted by an anomalous finding to problematize the relationship between their data-context understandings and the task context. They use different perspectives to try to make sense of the data point in the ocean – What were the numbers again? What’s our region again? What are we supposed to be doing again? Do we know how to do this after all? An implicit question that they do not ask at this point is: Can an earthquake happen in the ocean? This will be a crucial “suggestion” for making sense of the data as the activity moves on, and Dalia returns to thinking about this domain concept later in the period. But in the present episode, even though they do not problematize the earth science concept underlying their confusion, they do step back from their work to draw on other perspectives, in an effort to make sense of the data. Episode 3 (from Focus activity 2 – Mapping the plates)
A third example from a different activity shows reflection on data which is more convergent in connecting data to domain concepts through the inquiry task. In this episode, one of the researchers asks two students to show her what they’re doing. They have been assigned the task of drawing the outline of the plate on which their city, Tokyo, is located, using a data map with earthquakes plotted on it.
92 SM:
Tell me what you drew here
LaTanya:
Lines that showed up – all these dots
David:
Tokyo’s like right here. So we just followed all the dots. And then right here we weren’t sure, because there’s like nothing here, but then there were a lot around it
SM:
That’s interesting – of all those lines you draw, do all those represent boundaries of a plate?
David:
Well maybe – are we – are we supposed to do only one plate? Cause I’m thinking that, in the earth’s crust, there’s a bunch of plates.
… David:
I think that in the earth’s crust there’s a ton of plates -- like when we did the orange peel, we had a ton of ‘em. So there might be like two or three, or like a ton of plates all around here!
Here David has problematized his conception of the assigned task: to “do only one plate.” He has found the data problematic for doing this task, and has had trouble making sense of what looks like too many dots to draw one outline. LaTanya has characterized the task as drawing “lines that showed up” from “all these dots.” This may suggest a conception of the task that is defined in relation primarily to the materials (lines, dots). But David, expanding on LaTanya’s answer, brings in other elements in describing what they did, and generates a question which explicitly links the task to the data context: “Are we supposed to do only one plate?” The complicated pattern of data has him wondering. He refers to a model used earlier in the unit to represent earth’s crust (“like when we did the orange peel”), and to the nature of the earth’s crust itself. He has connected these perspectives on the task to propose a domain concept (“I think that in the earth’s crust there’s a ton of plates ”), as represented in Figure 5.6.
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Figure 5.6. David problematizes the task, and makes a web of connections in the data context.
David’s comments give us more explicit evidence of the trail of his thinking, whereas we must read more between the lines to understand Magalys and Dalia’s thinking in Episode 2. We must remember that David’s reflective connections would have been completely invisible to us if the researcher had not prompted him and LaTanya to make their thinking explicit. In the case studies of small group work that follow, we must keep in mind that most of the discourse we are looking at does not include this prompting. This means that we must propose assumptions about students’ thinking in these settings, and then look for other evidence to support or refute our assumptions. Characterizations become easier as we get to know individual students and their roles in group work. From episodes to case studies
These three episodes give a sense of the kinds of talk in small groups that occurred during the unit, and illustrate how our model can be used to characterize reflection in discourse. However, we cannot draw many conclusions from these “snapshots” of activity, other than the fact that reflection did happen at some points in time. But to understand how reflection relates to learning, we need to go beyond anecdotal episodes, and look for patterns in activity over time. The case studies move us beyond particular episodes as exemplars of reflection on data. Here we concern ourselves with the relationship between the development of group norms of interaction, and students’ changing roles in activity with data (see Figure 5.7). We will examine the process by which students change their mode of participation in small groups, specifically with respect to changes in activity that afford reflection.
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Figure 5.7. The case studies highlight the relationship between developing group norms in the task context, and developing student roles in the role context.
By looking at how group norms and student roles affect each other, we gain an understanding of the relationship between changes in group activity in the “task context” (guided participation), and changes in disposition in the “role context.” We will also see how both kinds of change – change in group norms, and change in student roles – affect learning in the “data context,” by affording and constraining particular kinds of reflective discourse. In this way we connect the reflection back to learning, which is our top-level goal for this model, while accounting for the complexity of activity across the three contexts. Our design interests lie with the role of designed curriculum artifacts in these processes of change. Our model shows the place of these artifacts (A) in the task context, suggesting that they play a part in shaping the kinds of learning that happen, but our cases studies must begin by characterizing learning – i.e., student change through activity. Once we understand how learning-to-be-reflective and learning-through-reflection took place, we will return to the role of artifacts in the Discussion section. Each case study presents the activity norms of a small group as a developing context for reflection. The learning of each group member is characterized as their changing role as a participant in small-group inquiry activity over time. The intention is to look not only at the story of a few individuals, but rather as patterns of participation which afford and inhibit reflection. As such, the case studies are named for their distinct patterns of activity – the “Comfort zone” and the “Confrontation zone” – rather than for their group members. To strengthen the claim of relevance beyond these specific students, the case study characterizations are re-examined in light of other student groups in section 5.4. Groups in the Boone classroom were the subjects of the two case studies presented here, though the framework for understanding them emerged from data analysis at all three
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schools. The Boone classroom provided us with the deepest data to work with: extended experience working with the teacher, the teacher’s perspective as co-designer, the largest coverage of unit activities, and the use of the Progress Portfolio for additional data on computer activities. To contextualize the case studies in terms of the chronology of the curriculum enactment, Table 4 shows the 36 days spent on the unit at Boone, with the Focus Activity days highlighted. The selected class periods were chosen for in-depth data analysis for a number of reasons. As Table 4 shows, the four focus activities are spread out over the life of the unit, giving us insights into students’ thinking at four different periods in time. The class periods most closely analyzed for each of the four activities are those in which the main mode of work was group work with data – this represents 15 class periods altogether. This is 42% of the total number of periods spent on the whole unit, and 65% of the total number of periods spent primarily on group work. In this sense, our sample of periods for analysis represents a significant portion of the total unit, supporting the claims that observations of changing behavior during these focus activities accurately characterize changes in behavior over the course of the unit.
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Table 4: Timeline of Earth Structures and Processes enactment at Boone school. Shaded rows represent class periods focused on in this data analysis. Single lines divide distinct curriculum activities. Double wavy lines represent a break of more than two days. Day 1
Date 10-21
Unit activity Top 10
Main mode of work whole class & groups
Focus
2
10-22
Top 10 & Myth readings
groups
3
10-23
Plot current earthquakes
whole class
4
10-26
Plot current earthquakes
whole class & groups
5
10-27
Clay models
groups
6
10-28
Clay models
groups
7
10-29
Clay models
whole class
8
11-09
Plot current earthquakes
groups
9
11-10
Clay models &
whole class
10
11-11
Clay models in Prog Port
individual work
11
11-12
Clay models in Prog Port
individual work
12
11-13
Crust drawing
individual work
13
11-16
Crust drawing
whole class
14
11-17
Models from drawings
individual work
15
11-18
Models from drawings
individual work
16
11-20
Plot current earthquakes
whole class & groups
17
11-23
Plate mapping
whole class
18
11-24
Plate mapping
whole class & groups
19
11-25
Plate mapping
groups
#2
20
12-01
Plate mapping
groups
“
21
12-02
Plate mapping
groups
“
22
12-03
Plate mapping
groups
“
23
12-04
Plate mapping
whole class
24
12-07
Boundary zones
whole class
25
12-08
Boundary zones
whole class
26
12-11
Boundary zones
groups
#3
27
12-14
Boundary zones
groups
“
28
12-15
Boundary zones
groups
“
29
12-16
Boundary zones &
whole class & groups
#1
#1
Plot current earthquakes
#1
Presentation prep 30
12-17
Presentation prep
groups
31 32 33 34 35 36
01-07 01-08 01-11 01-12 01-13 01-14
Presentation prep Presentation prep Presentation prep Presentation prep Final presentations Final presentations
groups groups groups groups groups & whole class groups & whole class
#4 “ “ “ “
act.
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5.2) Case 1: the “Comfort Zone” In order to look at an inquiry situation and try to make meaning of the complexity, a student must have a sense of comfort and confidence. Students often do not move beyond the point of awkwardness and discomfort in their roles as inquirers, particularly when it comes to problematizing things. Some students have enough will power and academic confidence to establish such a role on their own – they can jump into work with data and begin problematizing things, generating challenging questions and surprising observations, without much negotiation of this role with their fellow group members. But for many students, classroom inquiry situations begin with social negotiations of group norms and individual roles, which are a pre-requisite to problematizing anything. The first case study examines a group of two students, LaTanya and David, who established group norms for cooperative work which I have dubbed a “comfort zone” for work with data. Their group norms supported each of them in developing new roles in which they could work reflectively with complex data, in ways that they had not before. Their “comfort zone” mode of interaction mediated their mode of work with curriculum artifacts, promoting reflection in certain situations and inhibiting it in others. We will see how elements of each of these students’ personalities developed into more reflective dispositions through their engagement with the curriculum within this “comfort zone.” Who are LaTanya and David?
LaTanya and David had not been grouped together before this unit. Both were described by the teacher as “middle kids” academically, neither at the top nor the bottom of the class. LaTanya is one of three African-American students in the class, all girls. One of the other African-American girls, Charlisse, is also a member of our focus table group; the other, Felicia, sits across the room. Both Charlisse and Felicia often approach LaTanya for social chats about life outside of school – who came over to whose house last night, etc. LaTanya frequently jokes and chats with other students, and seems to have casually friendly relationships with a lot of the students in the class. She laughs a lot, and is described by the teacher as having “a great sense of humor.” David is one of seven non-immigrant white students in the class. He is usually quiet at his table (the teacher described him as “a mousy kid”), and often does his work alone while other students are working together. David’s individual assignments are usually complete and correct – as the teacher put it, “If you lay it out, he does it – he’s a really
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good kid.” When he does talk, his interactions with other students are almost always joking – he has a strong silly streak, often talking in funny voices or saying things sarcastically. David had been suspended from school by a prior teacher for a sarcastic comment he made to her. His quietness is not exactly shyness. LaTanya’s role in classroom activity early on: the “Frustrated Do-er”
LaTanya has many leadership qualities: outspokenness, communication skills, a sense of humor, and positive energy. She often pushes small group work forward toward completion, with comments like “Let’s finish this up” and “OK, we done?” This tendency often seemed, in early work during the year, to move her group’s work away from opportunities for reflection. In the words of the teacher, “LaTanya can be a leader … but she also gives up too easily… [When there is something that is hard to figure out], she will laugh and let it go.” [99-02-12] In other words, LaTanya did not tend to problematize much. LaTanya’s characteristic role early on can be described as the “Frustrated Do-er” – wanting to direct the action and move things along, but not engaging with the concepts underlying activity. Her “do-er” role is frustrated by problems with group dynamics – students not giving her the information she asks for, or a feeling that materials are not fairly distributed. LaTanya’s initial role:
§
Focus on her role with respect to group norms (fairness issues)
§
Wants to be central in completing task
§
Focus on materials in defining task, but without connections to data context
“Frustrated do-er”
In activities leading up to the Earth Structures unit, LaTanya’s attention was often focused on the niceness or prettiness of things – wanting to make a nice poster, noticing which group has the more attractive map, mentioning how cool the letters look, comparing which picture is prettier. She enjoyed making things in class that looked cool, and her pride in her work usually focused on surface features of the materials unrelated to the underlying content of the task. Focus Activity 1 provides a good illustration of this disposition. LaTanya was an active participant in group talk during Focus Activity 1, plotting current earthquakes. For
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example, during the first session of plotting, over a 20-minute period of group work, LaTanya contributed 56 of the table group’s total 256 comments during discussion – which is 30% more than her proportional share of table talk in a group of six (i.e. with 256 comments in a group of six, each student’s share of talk would be 43 comments). So LaTanya was participating in group discussion – but what was she talking about? Many of her comments were about the materials used for the activity, such as the following: “Ooh yes, we get some stickers! Ooh, lemme see, David! Gimme some stickers! [chuckling] I should take one and put it on [me]!” [pointing to other table] much nicer!”
“Awww, could we get that map?
Their map is so
“These [dots] are big” [98-10-26]
These comments suggest that she is focused on the materials, but is not connecting them with the task or the data (see Figure 5.8). Her comments are about surface features – how nice, how big.
“cool stuff” Figure 5.8. LaTanya focuses her attention on materials, but not in connection with the data context
Another focus of LaTanya’s attention was trying to make sure she got her fair share in the group, and voicing frustration when she felt she didn’t: “Bring the map over here guys!
Spread it out so everybody could see it.”
“’Scuse me, could we get one more map, because they’re like, so hogging it?” “Now I put the freakin’ dots on it, I don’t care what you guys say” [98-10-26]
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Here LaTanya forcefully stakes out a role for herself in the activity, and demands equal time with the materials. But as far as interpreting the meaning of the task, and making sense of the data, LaTanya mainly relies on her group-mates to tell her what to do: [motioning to area of map, asking David] “That’s what we’re doing?” “What color [should I use]?” “OK, point to Arkansas and pass me the thing that show what color” “Man, could you guys tell me what color to use?” [98-10-26]
In these interactions with the group, LaTanya does not problematize the data or the task for herself – she expects other students to provide the answers that require figuring things out. She has a relevant question about the materials: What color dot to use? But there is no “thing that show what color” – the students have not talked about the meaning of colors, and have no coding scheme. The question of what color to use became a focus of reflection for other groups in other classes, but here for LaTanya it is just a source of frustration – she asks her groupmates to tell her the answer, and they don’t. LaTanya is focusing on the materials, her role, and the group norms in terms of fairness – but she does not problematize the task for herself (only for her group-mates), and she does not connect with the data context (see Figure 5.9).
Figure 5.9. LaTanya’s early participation avoided the data context, and did not problematize tasks.
This characterization of LaTanya’s dispositions fits with the teacher’s observations about her state of mind before the unit. In the teacher’s words, “Where she was coming into [the Earth Structures unit], she was constantly arguing with other kids.” At the time of the unit, “she needed to get past horrible experiences working with other kids.” As far as engaging tasks and data only at the surface level, the teacher said, LaTanya was not very invested. She asks questions, but kind of just lets it go… She knows what she wants to do, but she also gives up easy. She doesn’t totally get in, she just kind of wades in the water. [99-02-12]
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We will see how LaTanya’s “wade in the water” disposition changed through the course of the unit. David’s role in classroom activity early on: the “Silent Thinker”
When grouped with others, David often did not work collaboratively – he was more likely to make fun of things, or drift away from the work and goof off with other boys. For example, on a small group assignment before the unit began, David finished a data analysis task quickly in his own notebook. He then watched quietly as the rest of his group went through a lengthy collaborative process of trying to figure it out, discussing the nature of the task and possible strategies for getting it done. As they finished, he said “I had that half an hour ago!” [98-10-05] At the beginning of the unit, David was a solitary worker, and a private thinker. He would usually remain mostly silent, both during whole-class discussion and during group work, except for occasional social joking around. Though he did not participate much, the teacher believed that David was doing a lot of thinking about class work in his silence, especially when faced with having to figure out something confusing: “David doesn’t let it go. He grapples with stuff constantly.” [99-02-12] We might say that David’s relationship with the data context was not mediated much by the group – his group role is the “Silent Thinker.” David’s initial role:
§
Non-participant in whole-class and small group discussions
§
Group interactions usually joking, and un-related to task context
§
“Cool ideas” (connections in data context) are individual, not shared in group discourse
“Silent thinker”
Since David’s reflections remained private, they did not contribute to the discourse of the class as a whole, and could not be examined by the teacher or other students. While other students were actively involved with classroom debates and discussions, David was quiet. The teacher wanted him to become more active and outgoing intellectually: “I wanted him to be more verbal, to explain, to take a leadership role… I don’t think he’s explored that leadership enough.” [99-02-12] In contrast to some of the vocal academic leaders in the class, she said, David “knew stuff, but just was not as confident verbalizing, arguing or getting into that debate group.” David’s quietness, however, did not mean that he had
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little to contribute. In the teacher’s words, “He’s got that kind of cool ideas going on in his head … he’s also too cool to express them.” [99-02-12] For example, in a characteristic whole-class discussion near the beginning of the unit (9810-23), the teacher led students through a remarkably lively discussion of the USGS web site. During the 38-minute discussion, students made a total of 155 comments, and more than half of the students made more than one contribution. David, however, said only one word: in response to the teacher’s question, he read a number off of the computer screen. In this, as in most whole-class discussions observed during the year up to this point, David did not bring his own thinking into classroom discourse. David’s reluctance to bring his ideas into classroom activity is even more noticeable in the context of table group work. His usual mode was to do the academic work quietly (and correctly) by himself, apart from the rest of the table group, and then participate in group process mainly by joking around. In small group work with Mario during the Staging Activities, David’s comments consisted only of asking Mario how to do things (“Like that? … Should I draw? … Should I draw a sun?” [98-10-23]). Again, David does not contribute his own ideas to the group, and does not talk much at all. In the first Focus Activity, plotting current earthquakes, during a characteristic groupwork session [98-10-26], David accounts for only 10 of the 256 comments made in the 6student group during 20 minutes of group work. This is about 1/4th of his proportional share of talk in the group. The only student in the group who participated less was Charlisse, who spent much of the period away from the table. The other four group members made 43, 56, 57 and 83 comments, respectively, showing the amount of active discussion going on around David, which he did not participate in. Of the 10 comments David made during these 20 minutes, five were sarcastic jokes unrelated to the work with data (e.g. “What’s wrong with being stubborn?”); two were a (repeated) sarcastic question about an earthquake location read by Joel (“Where the hell is Strawberry, Arkansas?!?”); and two were verbatim repetitions of other people’s comments. David thus made only one comment that contributed his own observations to the work with data: “There’s not very many [earthquakes on the list that aren’t in Missouri].” [98-10-26] This comment suggests that he is paying attention and making observations about the data, but only to the tune of one comment in 20 minutes! Thus we may safely say that if David was problematizing aspects of the inquiry situation, he was doing so privately, without contributing his thoughts to the group inquiry process. He stayed on the periphery of activity with data during the first part of the unit – keeping
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an eye and a hand in the work with data, but not sharing any of his thoughts. This limited his opportunities to make connections between what he was problematizing, and the reactions of his groupmates to his ideas. Developing group norms with data: the “Comfort zone”
Through the activities of the Earth Structures unit, David and LaTanya worked out a shared space in which each could develop a more reflective disposition for making meaning of complex data. This process began in Focus Activity 2, Plate Mapping, when LaTanya and David became partners. Early on they negotiated a friendly mode of work together. In the example below, LaTanya right away demands her fair role in the task of drawing boundaries – showing her characteristic frustration – and David is responsive to her: LaTanya:
Tokyo, we doin’ Tokyo, Tokyo! … OK, the plate boundary?
David:
Start like right here
LaTanya:
Let me do it some!
David:
OK, should I hold it down here?
[both draw lines]
[98-11-25]
In the collaborative space created here, David becomes more verbal than usual, and LaTanya pursues her questions farther than usual: LaTanya:
OK, go ahead -- right here too -- plate boundary’s right here, right?
David:
This whole line is a plate boundary
LaTanya:
Plate boundary’s over here?
David:
Just follow the black line
LaTanya:
Plate boundary’s over here too? …
David:
See, cause this line represents all of this – all of this… This would also be the plate boundary! {…} Then go down there …
Right here too?
[98-11-25]
Here we see the two students coming to a nice balance of roles. LaTanya’s high energy (“Tokyo, we doin Tokyo, Tokyo!”) keeps their work moving forward, but does not push David into passivity. David’s authoritative knowledge (“This whole line is a plate boundary”) does not push LaTanya to the sidelines, but is shared and explained (“See, cause this line represents all of this”). LaTanya takes on a follower role to David regarding correctness of answers and understanding of the task, but she also puts forth
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her own answers tentatively (“Plate boundary’s over here?”) and shows a sense of ownership. In contrast to other groups we will see later, the decision-making space is shared comfortably. These new norms afford reflection on the data context: LaTanya and David, for the first time in group work during the unit, are problematizing data patterns (lines of dots) and domain concepts (plate boundaries), as represented in Figure 5.10. LaTanya is talking about the task, and David is explaining his thinking.
Figure 5.10. LaTanya and David bring elements of the data context into their discussion of the task.
Group norms:
4.
Mutual support
“Comfort zone”
5.
Shared or jointly-developed conceptions of task
6.
Co-direction of work strategies
7.
Division of labor
8.
Joint, or uncontested, ownership of artifacts.
The “comfort zone” sustained reflection throughout the unit
This shared space was maintained by David and LaTanya throughout the rest of the unit. Here we see a smooth sharing of group talk and decision making during Focus Activity 3: David:
[points to computer screen]
LaTanya:
What, this?
David:
This whole thing.
LaTanya:
This, no …
David:
No, this I said. [points]
What is this?
These islands.
[points]
Those are islands aren’t they?
105 … LaTanya:
It’s a subduction zone
[David types “subduction zone”] [98-12-16]
Here we see both David and LaTanya jointly directing the decision-making in the work. They have maintained and improved their comfort zone since Focus Activity 2. Within this shared space, they are able to problematize different aspects of the inquiry situation. David problematizes data points, identifying them as real-world items (“What is this?” … “This whole thing. These islands”), and LaTanya recognizes a pattern, and makes the connection between the data pattern and a domain concept (“It’s a subduction zone”). These connections are represented in Figure 5.11.
Figure 5.11. David and LaTanya jointly make connections among many elements of the data context.
In another episode, we can also see them working out a joint conception of the task: David:
[points to text box] That’s where you tell the story.
LaTanya:
No, you do the boundaries, you know … He said do more than this.
David:
Then do more.
LaTanya:
David, where’s the map? Go get it. I need to know what is that around there. [points to part of clay model in picture] I need to go back, to our other thing with the [earthquake data]
[David finds that page and displays it] LaTanya:
OK, where’s our plate?
David:
[circles with finger]
Is this our plate?
[points]
This is our plate all around there. [98-12-16]
Here they problematize the task and their strategies for doing it – what are we supposed to do on this page, in this space? Should we put more there? (task ßà strategies) LaTanya raises the need for more data – problematizing the task in connection with a
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model of their plate, and realizing she needs other materials (“David, where’s the map?”). David gets the data for her; she problematizes the data patterns by questioning how they relate to a domain concept (“OK, where’s our plate at?”); and David provides his interpretation of the data (“This is our plate all around there”). In a comfortable flow of activity, the relationships among data, models, and concepts are explored, and they discuss how to complete their inquiry task (Figure 5.12).
Figure 5.12. LaTanya and David fluidly make meaning of their task and large amounts of data.
These kinds of “comfort zone” reflective episodes for David and LaTanya are found all the way through the final day of the unit. As we will see later, this comfortable shared space is not the only kind of reflective work mode which students created in this unit – others were less harmonious, though no less reflective. But this “comfort zone” worked well for these two students: it afforded LaTanya and David opportunities to reflect together on inquiry situations with complex data, in ways that they had not done before. The comfort zone has trouble with uncertainty
A major challenge for this group in working with data in this comfort zone was figuring out how to make room in their conversations for uncertainty about the inquiry. Resolving this challenge shaped the kinds of reflections that happened in LaTanya and David’s investigation. They needed to get past the urge to find a quick and easy answer, in order to make the complex data problematic. This presented a different challenge for each of them. David needed to get past his tendency to do his work quietly and alone, and his tendency to lapse into goofiness when working with others. We have seen that he was willing to grapple with difficult ideas, but not in a group. LaTanya needed to get past her focus on surface features, and her desire to finish quickly. She needed to be willing to work past her frustration in confusing situations.
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During Focus Activity 2, students were to draw their plate boundary predictions, using a big set of data on a map. The data map was created with the intent of making this task an uncertain one, requiring students to debate their lines (see Design Rationale secton above). In a conversation with Mario, David confronts a confusing area of the data map: David:
[to Mario] This would be a plate boundary! all could be a plate boundary!
Look, this
… Mario:
[pointing to an area without dots] What the heck is this? Is this the bottomless pit or something?
David:
I know!
Mario:
Right here it’s a bottomless pit!
David:
Put a question mark!
Mario:
[joking tone] “They say no one has ever lived here…”
There’s like nothing here!
[laughs]
[98-11-25]
Here Mario problematizes the data pattern, and David is able to join him – he combines his tendency to joke with the discussion of the data. He has benefited from Mario’s observation, and made it his own. (We will see later that Mario had benefited earlier from Joel’s observations in the same way.) David and Mario proceed to share their observation of this “bottomless pit” area with Juan, who then writes on the map overlay, “What is this?” – pointing to the bottomless pit. They are proceeding with the task as it was designed: problematizing uncertain data patterns for further investigation. But LaTanya becomes upset with Juan for writing on her plastic overlay. She does not so easily make room for uncertainty in the data – she is more concerned about somebody interfering with her materials, “messing up” her plastic: LaTanya:
[to Juan, angrily] Why, why did you write that for? do you mean, ‘What is this’?
What
David makes an uncharacteristic move at this point – rather than laughing at the conflict, as we would have expected earlier, he steps in to explain the data pattern to LaTanya: David:
Cause look, there’s all these earthquakes around here, and then there’s nothing here
… LaTanya:
[pointing to another area of map] So? There’s nothing here either! … Tokyo, Tokyo – OK, we’re about done, right?
LaTanya does not gain interest in the pattern, as the other three have. She explains it away (“So? There’s nothing here either!”). She is not interested in talking about the
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“bottomless pit” or what it might mean. She then proceeds to try to bring the activity to closure as quickly as possible (“OK, we’re about done, right?”), ending the discussion of the strange data pattern. LaTanya’s lack of interest in uncertain data is something we had expected from students, and tried to design for. To promote a sense of the validity of uncertainty (i.e. “it’s OK to not have a definite answer”), we designed one part of the plate-mapping activity (Focus Activity 2) in which students mark their plate lines in two colors – one for “Sure” and one for “Not sure.” Then, in mini-conferences between small groups, students are to report their sure and unsure boundaries to each other, compare their lines, and discuss where more data is needed. Neither David nor LaTanya engage productively with the “Sure – Not sure” activity and the mini-conferences. LaTanya at first shows no interest in participating in this activity (“I’m not gonna say nothing in my presentation!”), but as David begins to present their plate, she decides to jump in (“Oh, now I have to do it with you … this is what I’m gonna say”). However, after explaining the “sure” boundaries, she then turns to David to show the “not sure” areas – a concept that she is still not comfortable with – but David also refuses to characterize any lines as “Not sure”: LaTanya:
OK, this is where Tokyo is … The name of our plate is Azmina. And then – this is where we’re all sure of [pointing] – and then now David – you’re gonna show where we’re not sure of – and then you show the, uhm –
David:
We’re sure of them!
LaTanya:
[throws down pencil]
Why, then, you say it! [98-12-03]
LaTanya has lapsed into her mode of frustration with group-mates, and David has retreated from the idea that some of their lines are not sure (“We’re sure of them!”). He then lapses into his sarcastic mode of group interaction, when Ben tries to question his data interpretation: Ben:
One thing I’m confused of, [pointing to SE area of plate] how come there’s//
David:
//Because there’s … [adjusts loose pages of map] … when we did this they weren’t even taped on. So that’s why it seems to be – fucked up!
…
109 David:
Luckily Tokyo was in the middle of a bunch of earthquakes, … we go up – and go down, and around, and etcetera, etcetera, etcetera [pointing playfully around the plate] [98-12-03]
David and LaTanya both become frustrated with the activity – LaTanya because of her discomfort with her share of the task, David because of frustration over materials. The intended effect of validating “Not sure” interpretations did not happen for this group. Other students (Ben being one example) took to making these “Sure” and “Not sure” lines enthusiastically, but David and LaTanya never became comfortable with this activity. Validating differences of interpretation
A big step for David and LaTanya in embracing the uncertainty of data analysis came through a problem they faced twice as a group: having different interpretations of the data, or different “answers” to the data-analysis question. The first divergence came during the plate-mapping activity (Focus Activity 2) – here a researcher asks them to explain where they think the plate boundaries are: David:
I think that I know – cause look, there’s all these earthquakes around here, so this could be one plate, and where like none, it probably ends. And like right here, there’s probably one starting all over again {…}
SM:
OK. So you’re predicting possibly two plates in this area? And what would you say, LaTanya?
LaTanya:
One big one.
… LaTanya:
Cause there’s a lotta earthquakes. And so, and then it stops right here, so maybe there’s a plate right here, over there.
David:
No, I’m thinking like, this is where the plate ENDS, cause there’s none right here, but then they all start all over again. [98-11-25]
They have different interpretations of data patterns, and as a result they do not know how to proceed with the task. Their group norms do not allow for debating their different strategies or interpretations. This is an awkward moment for their group, as they do not know how to work together when they disagree. LaTanya and David are not sure how to proceed, given that they do not agree on their plate outline.
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Later, the teacher comes over to meet with them, and David raises their disagreement with her as a problem: Teacher:
[to David and LaTanya] …
Where do you think the plate is?
David:
… I think, I think there’s two plates over here, around here, but LaTanya thinks it’s all one.
Teacher:
OK. OK, well that’s something we’ll have to {work out} later …
David:
I think that this, right here, is all a plate [big area in the Pacific], but since right here there’s like nothing, except for like a few, and I think that this starts a new plate. [98-11-25]
By the end of the period, we see two different attitudes these two students are taking toward their difference of opinion. LaTanya settles on the stance that they each have their own idea – in fact, each their own plate – achieving a kind of closure on the question, and avoiding dealing with uncertainty: LaTanya: There’s Tokyo – and we named our two plates … [pointing to line] David plate’s right there – there go my plate
LaTanya has put the problematic data into a convenient box – “our two plates” – rather than problematize either of their interpretations. David, however, leaves the “correct” answer as an open question: David:
Well, we’re not sure yet, cause we have to add these [extra data pages]
David places the burden of resolving the uncertainty on their problems with the materials – they need to add more data pages in order to figure out the right line. Help from the teacher: Validating different interpretations
The second divergence of their interpretations comes during Focus Activity 3, when they have to decide which way their plate is moving. The teacher again comes in to help them mediate a difference of opinion, and helps them make their interpretations concrete in the form of separate Data Interpretation pages in the Progress Portfolio: Teacher:
So do you agree David? Or do you want to do something else? Do you want to make a different prediction?
David:
There’s only one thing, like, cause I disagree on the plate motion.
111 Teacher:
[to LaTanya]
OK, is your plate motion labeled on here?
LaTanya:
Yes.
Teacher:
OK, prediction of motion. Let’s do the same all over again, but for David’s now.
[Teacher captures the clay plate picture into their Portfolio and makes a separate page for David] Teacher:
[to David] So then you just have to explain what direction you think it moves in. OK. And then we’ll call this … “David’s predictions of motion.” So then you can put your predictions.
Here the teacher validates the idea that the data can support different interpretations, and encourages them to explain their different positions within their work product. This intervention is a very effective repair to the breakdown in this group’s “comfort zone dynamics (see Figure 5.13), and enables them to continue with their inquiry project.
Figure 5.13. The teacher’s modeling of how to present separate interpretations re-establishes this group’s “comfort zone” mode of activity.
This permission to disagree helps David and LaTanya maintain their comfort zone – they do not have to argue about who is right, but can keep both of their interpretations within their project. They maintain separate “David’s prediction” and “LaTanya’s prediction” pages right through the final presentation. This resolution of a disagreement highlights both a strength and a weakness of the “comfort zone” for work with data. Maintaining separate interpretations of the data enables David and LaTanya to stay within their comfortable space for inquiry discussion, avoiding a potential conflict. On the other hand, it does not allow them to push their investigation to the next level of reflective consideration – i.e. comparing the two predictions to see which is better supported by the available data, or arguing their positions using evidence. This would likely have pushed David and LaTanya out of the comfort zone, either making LaTanya mad or making David withdraw. However, had
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they done so, they might have found a major oversight in David’s boundary line, and could have developed a more coherent analysis of how their plate moves. Preparing a final presentation: Reflection on models, avoidance of data
The activities with data were designed to give students a wide range of representations of data and concepts, in order to help them build connections. However, different students found particular representations more useful than others as objects of reflection. For a variety of reasons, David and LaTanya both spent more time problematizing models and concepts than data points and data patterns. For LaTanya, the models that they created – their plate map, the clay model of Japan, and the clay model of their plate – seemed to be highly-valued artifacts of the inquiry. Many of LaTanya’s reflections occurred while she was looking at a photograph of her clay plate model in the Progress Portfolio. These model-making activities tapped into LaTanya’s pride in creating nice-looking things in the classroom, as we see in comments like this: LaTanya:
[showing
plate model]
It took me three days to do this! [98-12-03]
LaTanya:
How did you guys name y’all’s plate? … Look what I named ours … Azmina.
Shami:
Who’s Azmina?
LaTanya:
My cousin
Shami:
Why’d you name it Azmina?
LaTanya:
Cause she’s pretty [98-12-03]
LaTanya:
Go to ‘LaTanya’s clay model.’
That’s what I did. [98-12-16]
At times LaTanya’s affection for these models got in the way of problematizing the data and concepts which they were made to explain. For example, she spent time and concentration on deciding the right name for her plate, but this ended up being time taken away from figuring out the data (see Figure 5.14). However, these non-data-context connections with classroom artifacts also provided valuable connections for LaTanya between the task context and her non-school identities in the role context.
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Figure 5.14. LaTanya connected classroom artifacts with her non-school identity.
However, this identification with the material products of activity also could serve as a lever for promoting reflection in the task context and the data context: “So something’s going on down here.
On my clay model, yes it is!” [98-12-17]
In this way models often served as an anchor for her in thinking about the concepts, as they were intended to do. LaTanya’s personal-life connections and her data-context connections to artifacts were not incompatible. We will return to this theme below. For David, the domain concepts explained by the teacher in mini-lessons – such as the concepts of subduction zone, buckling zone, etc – became a main focus of his thinking toward the end of the unit. He often used the hand-motion models of each type of plate boundary zone to describe them, and he spent much of his time in the Progress Portfolio writing down what these zone types were. David and LaTanya together spent a good deal of time writing concept definitions from David’s journal into their Progress Portfolio file. For David and LaTanya as a group, reflections about models and domain concepts often pulled them away from problematizing the data they had been studying. For example, in preparing their final presentation (Focus Activity 4), they left out many of the reflective observations about the data they had made up to that point, and focused primarily on defining and demonstrating domain concepts. In other words, the Presentation Preparation activity failed to prompt reflection to the data patterns explored earlier. In an extended episode from Focus Activity 4, shown in Table 5, we can see how reflections on data during Presentation Preparation were avoided by this group, even when prompted. This takes place after David and LaTanya have spent a long time typing in definitions of the zone types from David’s science journal into the Progress Portfolio. Their presentation contains little explicit discussion of data patterns. The researcher (JR) comes over to prompt them to use data in their discussion, suggesting that they use a
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particular strategy: connect their zone definitions with data images from their plate investigation. Table 5: LaTanya and David avoid explaining data in their final presentation Student LaTanya: [reading] David:
discourse
Strategy
“Another is a buckling zone”
“Another is a buckling zone. –“ [typing]
David:
task
DEFINING DOMAIN CONCEPTS
That is when
LaTanya: This presentation better be done by today! … [looking at instructions] Let me see, we need detail, effort – Details! Lots of details!
for
“ FOCUS ON FINISHING
No!
LaTanya: Yes, details JR (researcher):[coming over] David:
[chuckles]
Yes!
What details?
PROMPT TO REFLECT ON TASK
I don’t know!
LaTanya: We have details about each zone – [to David] keep typing, you keep typing JR:
Can you show an example of each zone?
STRATEGY SUGGESTION
–
USE
EXAMPLES FROM DATA
LaTanya: We don’t -David:
We didn’t show – you mean, write it down, or --?
LaTanya: No, pictures!
DEFINING CONCEPTS UNDERSTANDS SUGGESTED STRATEGY
David:
JR:
David:
Yeah, we’re thinking like, we can pick up the model and show it [gesturing with hands]
USING MODELS FOR DEFINING
Or, what about when you’re on the computer, since you’re there now – what can you show – what details could you show to explain what you’re talking about? Pretend you’re a 10-year-old kid, and you’re sitting there listening – and you said, a buckling zone is what?
PROMPT TO REFLECT ON
When two continental plates collide//
DEFINING CONCEPTS
LaTanya: //and it forms a mountain//
[hand gesture]
CONCEPTS
PRESENTATION TASK
USING MODELS FOR DEFINING CONCEPTS
115 David:
[hand gesture] //and they buckle up and forms a mountain
JR:
OK. Can you help me understand that by showing me a picture of one? Do you have one in there anywhere?
David:
No
JR:
No?
LaTanya: Not in this JR:
PROMPT TO USE DATA
AWARENESS OF THE DATA
Which zones do you have examples of on your plate?
LaTanya: So far? JR:
“
Oh, on our plate?
Subduction zone
Can you show a subduction zone?
CONNECTS DATA TO CONCEPTS PROMPT TO EXPLAIN DATA
LaTanya: Oh yeah, I could show you a subduction zone. [opens a page with lots of earthquake data displayed] That’s a subduction zone, and that’s a subduction zone, and like that …
CONNECTS DATA TO CONCEPTS
JR:
CONFIRMS STRATEGY
That’s the kind of detail you want to have
LaTanya: OK David:
And then we need like – I don’t think we have any buckling zone on our plate. [opens another page]
LaTanya: What is it, just include everything that we have on ours – before we run out of time? [pointing to clock]
CONSIDERING STRATEGY
FOCUS AGAIN ON FINISHING
[teacher reminds the class that they need to have both a compter presentation and a physical presentation] LaTanya: Oh my gosh David! gonna do! David:
Physical!
What are we
FOCUS ON FINISHING
Physical, we just tell the story …
LaTanya: Don’t we need some pictures … [99-01-12]
This discussion shows some productive reflections when they are prompted: LaTanya identifies a series of subduction zones from data, and David notices that there are no buckling zones on their plate. They seem poised now to gather “some pictures” – data images showing the boundary zones around their plate.
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But they do not sustain this mode of reflection on data – when they realize they are running short on time, they stop looking over their data collections, and focus instead on a lengthy process of creating large paper models to demonstrate how a subduction zone is formed. Both of them start excitedly discussing how they could make cool paper models showing how mountains appear near plate boundaries. These kinds of discussions did provide opportunities for reflection among three elements of the inquiry situation: models, domain concepts, and real-world items (see Figure 5.15). However, by missing opportunities to connect these with data points or data patterns, they missed some opportunities to build stronger connections in their domain understandings. Their final presentation focused much more on explaining domain concepts, than on illustrating these concepts by showing their observations from data.
Figure 5.15. David and LaTanya’s focus on models in Activity 4 connected to concepts, not data.
It is worth noting that their avoidance of more data analysis in this final Focus Activity may have been partly due to classroom logistics. Both LaTanya and David had several absences during the final weeks of the unit, and they were only together in class for one day of the intensive computer work with data during Focus Activity 3. Had they had more time to collect data, they might have featured it more prominently in their presentation, and spent more time reflecting on it in their presentation preparation time. Summary: the “comfort zone” norm of group activity
The case study this far has focused on the development of group norms within the task context. We have seen how this group established a “comfort zone” for working together in activities with big data sets, adopting complementary roles. We have seen their difficulties making sense of tasks in which answers were uncertain, and we have seen how the teacher guided them in dealing with multiple interpretations of data. We have also seen how they settled into a comfortable mode of reflecting on unambiguous models and concept definitions, avoiding some of the more problematic discussions of data.
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Learning outcomes: Changes in roles, dispositions and understandings
Now we turn our attention from the development of group norms on the plane of guided participation (the task context), to evidence of individual learning and change on the plane of participatory appropriation (the role context). So what did LaTanya and David learn during this inquiry unit? What understandings, abilities, and dispositions toward data did they come away with? What was appropriated from the patterns of social activity we have discussed so far? To answer these questions we can examine both the reflective episodes during the unit, and the understandings each of them showed in individual interviews after the unit. LaTanya’s emerging disposition to problematize data and concepts
One change during the unit was LaTanya’s visible development of a disposition to problematize data, models, and concepts. She moved from a focus on surface features of the materials, and a disposition to finish activities as quickly as possible, to a sustained interest in figuring out confusing aspects of the investigation. In Focus Activity 2, LaTanya showed a tentative interest in explaining her observations, but she was still grappling with the words, the concepts, and their relation to the data: SM (researcher): And where do you think the boundaries of the [plate] might be? LaTanya:
The plate boundaries? – the boundaries?
Where do you think the edges of it
SM:
Yeah – which would be like the edges of it.
LaTanya:
Maybe – maybe [pointing] – hold on, I gotta think about it for a minute. Maybe right here – somewhere?
SM:
Uh-huh – and why are you thinking that?
LaTanya:
Cause it’s a lotta, there’s a lotta, there’s a lotta – what does these dots stand for again?
David:
Earthquakes
LaTanya:
Cause there’s a lotta earthquakes. And so, and then it stops right here, so maybe there’s a plate right here, over there. [98-11-25]
Here we see she is still uncertain about the relation of data points to their referents (“what does these dots stand for again?”), but she is beginning to generate tentative explanations for data observations (see Figure 5.16).
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Figure 5.16. LaTanya’s tentative connections in the data context in Focus Activity 2.
By Focus Activity 3, LaTanya shows a more confident and adept approach to relating data to concepts. LaTanya contributes her understanding of subduction zones to a wholeclass discussion, relating data patterns to domain concepts: Teacher:
So what kinds of zones … how do you know they’re subduction zones?
LaTanya:
Cause they’re a nice line of volcanoes [98-12-11]
This is the first time LaTanya has answered a “data-context” question during whole-class discussion, and suggests a new level of confidence in her understandings. LaTanya’s change in understanding and confience was accompanied by a change in her disposition toward tasks. In group-work toward the end of the unit, LaTanya is very focused on the work of documenting the motion of their plate She no longer shows her earlier desire to finish activities as quickly as possible: LaTanya:
… subduction zones .. We gotta get some more of these! … Hawaii’s right there – hmmm – Come on, I want to go to some of these. Where’s our plate at? Is this our plate under here? Oh, this is it. Oh yeah, we gotta name the motion of the plate?
… David:
Alright, that’s enough
LaTanya:
No, we gotta know what’s down there
David:
… Why?
LaTanya:
Hey go to that big world map [98-12-17]
Here David pushes for quick closure (“Alright, that’s enough”), but LaTanya wants the explanation to be complete, rather than just finished (“No, we gotta know what’s down there”). This is a marked change from her earlier disposition to finish as quickly as
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possible. She has problematized the task of explaining the processes going on on her plate, in a way that was rare for her earlier in the unit. She connects it with materials and strategies (“go to that big world map”), in addition to the underlying meanings in the data context (Figure 5.17).
Figure 5.17. LaTanya’s more reflective engagement of tasks.
Within the data context, LaTanya problematizes patterns of data which are not easy to explain. She also seems very confident in her ability to figure out this confusing area: LaTanya:
[making an earthquake data query in the software] hold on, hold on – cause these dots are pretty small [chooses a larger dot size and displays data] … So something’s going on down here. On my clay model, yes it is! Concentrate David!
… LaTanya:
What’s going on down here? wanna find out everything. zone, subduction zone …
It’s a lot of volcanoes … I Subduction zone, subduction [98-12-17]
In these few reflective comments, LaTanya shows that she is problematizing not only the task, but also several elements of the data context, making many connections: §
a real-world place (“Hawaii’s right there”), with reference to data patterns (“I want to go to some of these”) and domain concepts (“where’s our plate at?”);
§
a data representation (“these dots are pretty small”), with reference to a data pattern she wants to be able to see;
§
a data pattern (“something’s going on down here”), with reference to a model of her plate prediction;
§
a different data pattern (“It’s a lot of volcanoes”), with reference to a domain concept (“subduction zone, subduction zone, subduction zone”).
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The reflective connections LaTanya makes in this brief period represent a significant tying together of perspectives within the inquiry situation. But a reflective disposition did not replace her other dispositions
But it is important to understand that LaTanya’s development of a more reflective disposition in this unit did not replace her earlier dispositions – rather, it developed out of them. Throughout the unit she maintained her focus on an attractive surface appearance of the artifacts of inquiry. Even in the final presentation she spent a good deal of computer time changing the font size and type style of the letters (“I want everything to be in STYLE!”). However, whereas earlier this focus was completely apart from the substance of the investigation, LaTanya’s focus on style merged with her process of interpreting data. For example, during the plate mapping activity, LaTanya became concerned about the lines they were drawing on plastic becoming too “sloppy” or “junky”: LaTanya:
OK, I got some 409 [to erase with]. thick. OK, write it over
I drew the line too [98-11-25]
This concern matches with LaTanya’s focus on surface appearances, but it also becomes important to the data analysis they are doing. Too thick of a line over-simplifies the decision of where to draw the line – it also obscures the important distinction of which things are on which side of the plate boundary. In effect, sloppy lines serve to deproblematize the task. LaTanya recognizes this problem during a discussion between their table group and the teacher, whereas David and Mario do not: Teacher:
I’m not sure, I’m not convinced. Cause I look like, this mark [Tokyo] is more on THIS side of this line, and Honolulu’s on THAT side of that line
LaTanya:
[erasing with towel]
David:
But look over here//
Mario:
//I think it probably would go in there [points to Asia]
Teacher:
So maybe there’s a plate line this way.
LaTanya:
Look at all this marker
Let’s make it clearer.
… David:
//I think it MIGHT be going this way! [points to Asia]
Teacher:
I don’t know. I think maybe you need to know where Tokyo is more specifically, though.
121 LaTanya:
Yeah, cause this [Tokyo dot] is like a big old – [98-11-25]
LaTanya grasps the teacher’s point – that they cannot interpret which plate Tokyo is on until their markings are more clear. Her concern for clear lines and neat dots in the plate mapping activity comes up again the following week, during a mini-conference: Ben:
Do you agree with us?
LaTanya:
About what!?
Ben:
Our plate boundaries
LaTanya:
You know what I think, I think y’all should erase some of this and make your lines very clear so I could see –
David:
We’re not sposed to erase em
Ben:
We can’t erase them
[Ben traces again around plate with marker] LaTanya:
See you making too many lines!
Ben:
This is the line, all the way from here –
LaTanya:
That’s too many lines, I’m not paying attention
Ashish:
That’s around Africa, isn’t it? mmmm-Middle East? … whatever?
LaTanya:
Ha ha, I know man, this an ocean … [points to Atlantic part of plate] this side here – I don’t know what y’all did! … You know what I don’t get? You guys have too many lines … too junky.
Around Africa and the
[98-12-03]
Here it is clear that she is questioning the other group’s work not just based on style, but also on its value as a model to represent the relation of the plate to the Atlantic Ocean (see Figure 5.18). LaTanya is absolutely right in her critique of the other group’s plate lines – they are too sloppy to be useful when they later have to determine which kinds of boundary zones they are.
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“cool stuff” Figure 5.18. LaTanya problematizes the sloppy plate model within AND outside of the data context.
This shows how a more reflective disposition in interpreting data does not have to replace students’ current dispositions, but can build on them. LaTanya’s concern for neatness becomes what Dewey might have called a “native resource” for reflectiveness in her personality – one that can be developed through inquiry experiences from a contentfree concern with appearances, to a productive habit of accurate representation. Also, different dispositions toward data co-exist at the same time. We have seen earlier how David and LaTanya steered away from problematizing data in Focus Activity 4 (Presentation Preparation), after having done the kind of reflective work we have seen above in Focus Activity 3. This should not be surprising – research has shown more- and less-adaptive reasoning strategies co-existing for long periods of time (Kuhn 1993). Changes in LaTanya’s domain understandings
What did this more reflective disposition help LaTanya to learn? She showed an ability to draw on many of the experiences and concepts to explain things in the world in the post –interview. JR:
Do you think that the ocean floor is the same everywhere, or do you think that it’s deeper in some places and shallower in other places?
LaTanya:
I think it’s probably shallower in some other places
JR:
Where do you think it would be shallow and where do you think it would be deep?
LaTanya:
It would be deep in here – right down South America right here [points to map]
JR:
And how do you know it would be deep right there?
LaTanya:
Cause remember when we were doing the computer, and this is a trench? And a trench means like it’s deeper, so the
123 water probably WOULD be deeper. And you could see those lines of dark blue and light blue. [pointing to topographic lines on map]
Here LaTanya reflects on prior experiences (“remember when we were doing the computer?”), data on a map (“you could see those lines of dark blue and light blue”), and domain concepts from the unit (“a trench means like it’s deeper”). She uses the connections among these to find a place where the ocean would be deep, and to explain her observation. However, she is less sure of herself in trying to explain a mechanism: JR:
What might cause it to be deep or shallow?
LaTanya:
I don’t know, maybe it’s because of, uh –- maybe because of the plates?
JR:
OK, so how would that work – how would that make it deep?
LaTanya:
Cause me and David did our plate – right on here and then over -- [showing near and far sides of map]
… JR:
So how might the plate make it deep?
LaTanya:
It’s like, here, I don’t know what happened to make it deep [looking closely around South America]
JR:
OK, take a guess
LaTanya:
Cause it’s a trench? It’s a trench right here, and a trench means it’s very deep – so maybe the water became deep along the coast. [pointing]
LaTanya is tentative, seeming first to guess (“maybe because of the plates?”), then fishing for a connection to her work with David (“Cause me and David did our plate”). She does not connect to the concept of subduction zones to explain how a trench is formed, despite the fact that this process was featured prominently in her own final presentation. These connections are still tentative for LaTanya, although many of the conceptual pieces and data analysis abilities are there. LaTanya’s reflective disposition in reasoning from data is evident later in the interview, when she is asked to predict where on a world map we might expect to find volcanoes: JR:
Where would you predict volcanoes might erupt, on this map?
LaTanya:
Right – volcanoes - they’d be right here. [points]
JR:
OK, … anyplace else?
LaTanya:
Uh-uh. Volcanoes -- in here too – in, um Europe.
JR:
OK, why do you think there’ll be volcanoes here?
Or is that the only place?
124 LaTanya:
Because, I’ll show you on this picture [turns to big wall map] - there’s a trench too, on this picture, and it has deeper water right here, like in that other graph that you showed me – and, since it’s two plates, it crashes into each other, and there’s volcanoes.
JR:
OK … And why do you think there might be volcanoes right here?
LaTanya:
Because, in – the last time you showed me this, you showed me another picture, with a lot of red dots for the volcanoes. And plus Russia has, like a lot of mountains, see all those mountains right there? [points to wall map] And it has a plate under it, and the plate has, Indian Ocean, too, and they each crash into each other, they form a mountain. Oh right, it’s some right here too [points to another place on map] – volcanoes.
JR:
Why do you think … here in the ocean?
LaTanya:
Because it’s the two plates – it’s like, it’s a continent? You can just picture like this going under the continent, and then you have Atlantic Ocean [pointing], which, they both have plates on ‘em. So they crash into each other, and move into each other, they form a volcano in the ocean.
Here LaTanya uses several sources of information flexibly: §
information from two different maps (“on this picture … like in that other graph”);
§
her memory of a data map (“you showed me another picture, with a lot of red dots for the volcanoes”);
§
knowledge of places in the world (“Russia has, like a lot of mountains”, “Atlantic ocean”);
§
domain concepts from the unit (trench, plate); and
§
a detailed mental model of plate motion (“You can just picture like this going under the continent”).
This explanation of her prediction of where volcanoes occur shows a complex web of reflective connections LaTanya has made, using all five elements from the data context to explain her prediction (Figure 5.19).
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Figure 5.19. LaTanya makes many data context connections in explaining where volcanoes happen.
It also shows gaps in her learning – she uses a description of subduction (one plate going under another) to describe areas that are formed by different kinds of plate motion (buckling in India; rifting in the Atlantic Ocean). LaTanya and David focused mainly on explaining subduction in their presentation, and identified only subduction zones on their plate – and so she over-generalizes her knowledge of this zone to explain other data. However, she has clearly developed a very detailed schema about earth structures and processes which could be improved by future learning. David’s emerging participation in reflective discussion
Like LaTanya, David showed a significant change in his mode of group-work with data over the course of the unit. He became more verbal in group and whole-class discussions, and talked more about the content and concepts of academic tasks. This change seemed to begin in the context of his group-work with LaTanya, but it grew to include the table-group and whole-class context as well. Participation in whole-group discussion
We have seen how David’s participation in classroom discussions was minimal before and at the beginning of this unit. But by the end of Focus Activity 1, David starts to contribute in discussions of the Earth Structures investigation. By the end of the unit, he is a regular contributor to debates about how to analyze the geologic data, voicing creative hypotheses and initiating conversations with his group-mates about the investigation. David begins contributing more in whole-class discussion by responding to the teacher’s questions about the ongoing inquiry, such as “Who can remember what we were working on yesterday?” David states the current inquiry task in this way on a regular basis as the unit progresses, often being the first contributor to whole class discussion for the period (11/25, 12/3, 12/11, 12/17). But in addition, David begins to contribute his knowledge to
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the conversation. On 12/11, for example, David contributes five times to the whole-class discussion, the most contributions of any student during the 34-minute conversation. Each contribution provides relevant information: Teacher:
OK, it doesn’t ooze up, Billy did a drawing for us the other day, it doesn’t ooze up where the subduction actually happens, where does the volcano come up? [David’s hand goes up] David?
David:
Because when they, uh, {inaudible} crack? uh, magma goes up -- Makes a volcano …
And then the, [98-12-11]
Compare this pattern of talk (five comments contributing ideas) with his one contribution on 10/23, a one-word response to a direct question. It is worth noting that David’s contributions on this day (12/11) do not tend to be as reflective as those of some other students. They tend to involve reporting back facts that had been discussed in a previous day’s discussion, rather than the connections to work with data and personal experiences that we see from some other students. However, as the unit progresses, David moves beyond reporting information from his notebook, and brings his own creative thinking into whole class discussions. For example, six weeks into the unit, David has been wrestling with an original theory about plate motion, trying to make sense of a confusing pattern he has observed around his plate (subduction zones on three sides). He has been wondering whether a plate can move in different directions on different days, and he introduces this idea into the wholeclass discussion, asking whether this is possible. Here David has begun to do what the teacher had hoped for him – to introduce his “cool ideas” into the lively flow of discussion which characterizes this class. David has derived his theory that plates can change direction from the fact that he and LaTanya found subduction zones on three sides of their plate. His theory of plate motion indicates a number of reflective connections he has made: 1. connecting an observed data pattern (volcanoes next to earthquakes all around the Pacific) to a domain concept (subduction zones) 2. connecting the domain concept (subduction zones), to a data-based model (his and LaTanya’s plate), to another domain concept (plate motion direction)
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3. identifying an anomalous data pattern (subduction zones on three sides of the plate), attempting to coordinate theory and evidence, and generating an explanation to account for the anomaly This web of connections is represented in Figure 5.20. Whereas before this unit David might have developed such connections in his mind, he would not have brought this set of ideas into the group discussion – a process that forces him to make his ideas concrete, and enables other students to build on them. David held onto this theory through the end of the unit, recording it in their Progress Portfolio file, despite the fact that it was different from LaTanya’s prediction of plate motion. But most importantly for his role development, David shared his “cool idea” in whole class discussion.
Figure 5.20. David’s reflective connections in generating his “different directions” theory. Participation in the table group
More dramatic was David’s change in his role in group work with data. To characterize this change we can compare his participation in table talk, during equivalent table-group work sessions at different points in time. Earlier we saw David’s participation at his table relative to the other table-group members at the beginning of the unit: on a characteristic day (98-10-26), he had contributed only 1/4th of his proportional share of comments in a characteristic 20-minute period (i.e. 10 out of 256 comments, in a group of six); half of his 10 comments on that day were sarcastic jokes unrelated to the task. Only 1 of his comments on that day was a contribution to the group’s inquiry work. Now we look at a characteristic table-group-work session from halfway through the unit (98-12-03). During this period, David participated in three different groupings of 3-to-5 students, discussing their plate mapping products, for a total of 17 minutes. During this time, David made 40 comments, out of a total of 151 for all students. This represents 26% of all student talk, or 2.4 comments per minute (compare with 0.5 comments per minute in the earlier session). David’s participation now represents exactly his
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proportional share of talk over this time (100.2%) – compared with only 25% of his proportional share in the earlier session. More importantly, the nature of David’s contribution in the table-group setting has changed. Of his 40 comments during this period, fully 50% of them were contributions to working on the investigation; 20% were jokes; and 20% were social chat. But significantly for David, all of his joking and social chat was related to the content of the inquiry. These were comments like: [moving plastic off map]
“Oh my god – the plate can move!”
“Luckily Tokyo was in the middle of a bunch of earthquakes, … [in silly voice] we go up – and go down, and around, and etcetera, etcetera, etcetera!” [points playfully around plate]
These kinds of silly comments are in contrast to his jokes at the beginning of the unit, which were 100% un-related to the work at hand. Of David’s 40 contributions to table talk on 98-12-03, only one was completely unrelated to the inquiry work. We noted above that David’s academic disposition had previously been to work privately, and his group participation disposition was mainly joking and non-academic. It is important to note that the change we see here in David’s mode of group-work is not a matter of abolishing his old disposition in favor of a new reflective one. Instead, he builds on his silly social personality, but moves his joking into the academic sphere – even joking on-task. This shift also makes room for him to contribute his serious ideas in classroom talk – exactly the goal the teacher had for him at the outset of the unit. Like LaTanya, David’s increasing disposition to reflect in group-work with data draws on his “native resources” – humor, sarcasm, a critical mind, and an enjoyment of social interaction. Changes in David’s understandings
David was able, after the unit, to flexibly apply domain concepts, explanatory models, and observations from data to explain and question things in the world. His pre-unit understandings of earth structures and processes were fleshed out in many directions. Note the post-unit causal model that refines his pre-unit conception of earthquakes: QUESTION: Can you explain what an earthquake is? PRE-INTERVIEW ANSWER: David:
Well, I’m not sure, but I -- like when the earth kind of shakes, not the whole earth but just parts of the land -It does a lot of damage, it could crack the ground and stuff like that
129 POST-INTERVIEW ANSWER: David:
It’s when two plates collide, and it like causes a lot of friction, and it makes like the earth shake.
David’s network of conceptual referents after the unit includes connections among all elements of the data context: real-world items, data items and patterns, models, and abstract concepts. In specifying where earthquakes happen during the post-unit interview, David makes connections between these data context elements and prior experiences in the investigation: JR:
What kinds of places do earthquakes happen?
David:
It happens all over the world!
JR:
All places equally, or some places more than others?
David:
Some places more than others. Most of the time around the coasts, because those have a lot of subduction zones. The continental plate goes -- the oceanic plate goes under the continental plate
JR:
Where would that be?
David:
Like when we were doing the project with the different plates, I had this plate [puts hand on Pacific Ocean] … And it went, see, it came all the way over here, and there was subduction zones ALL around here. And of course here, and up there.
[chuckle]
where would you expect?
David also showed a more reflective mode of drawing conclusions from complex visual data. His puzzling through a prediction question (below) includes recognizing gaps in his own understandings: JR:
Where would you predict volcanoes might erupt, on this map?
David:
All around the coast of South America, maybe around the coast of Africa. I’m not sure about here though. There might be volcanoes there, I’m not sure.
JR:
Up here in Europe?
David:
Or maybe like around here, because -- no [pause, mumble] that’s a different thing
JR:
Why do you say no?
David:
Cause I was gonna give an explanation, but it’s not --
JR:
What were you gonna say?
David:
I was gonna say because there’s the mountains there, that I was thinking of the subduction zone, when the volcano pops up.
Anyplace else … ?
You had said maybe along here...
130 JR:
OK, so this is not a subduction zone?
David:
[nods]
JR:
So there’s not volcanoes there?
David:
Well, think think had a
there might be. Because I remember -- I forgot -- I the buckling zone had scattered volcanoes. And I that the volcanoes that are right here [Himalayas] buckling zone, so it might have scattered volcanoes.
His hesitation in this answer suggests that he has caught himself over-generalizing the “subduction zone” explanation for volcanoes. This over-generalization is a mistake also made by LaTanya, and it is traceable back to their group’s comfort-zone interactive mode. Unlike LaTanya, David has developed enough depth to his data-context understandings to allow him to recognize this error for the first time during the postinterview. In addition to questioning his understandings on his own (as in the prediction above), David shows a disposition to problematize his understandings with respect to contradictory data. When he is shown the data to compare with his prediction above, he recognizes both the accuracy of his uncertain prediction of “scattered volcanoes” above, but also a problem with another of his assumptions – that there would not be volcanoes in central Africa: JR:
This map shows places where volcanoes have erupted. What do you notice when you look at it?
David:
Um, see, like right here there’s the scattered volcanoes, and then there’s some in the ocean, and along the coast.
JR:
Is there anything that surprises you about the volcano locations on this map?
David:
Like before I said I don’t think they’d be right here [central Africa], but there ARE. Right in the middle.
JR:
Why do you think that might be?
David:
Maybe because they might be – see, like right here there’s the mountains, so maybe that could be a buckling zone, and there were scattered volcanoes.
This is significant in that David is able to flexibly reason within the data context, keeping his understandings open to question even with respect to concepts that are wellunderstood. Most significantly, the post-unit group activity also shows changes in David’s disposition to put his understandings forth in a group investigation. In the post-unit group interview
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activity, he actively states observations, possible explanations, and suggestions for inquiry strategies throughout the 40-minute investigation. Furthermore, he engages his fellow group members in debate about the data (“No, but we circled HERE with a lot of kids for low income!” “I’m saying that’s not a good REASON, why you said!”) This kind of active joint engagement of the data is a practice absent from his pre-unit participation in this activity. David’s increased disposition to communicate with others about data analysis extended outside the classroom. Weeks after the unit ended, upon hearing news of a devastating earthquake in Colombia, David’s mother informed his teacher that he had excitedly explained to her the reasons why the earthquake would have happened there, the fact that it was probably a subduction zone, and its relationship to the Andes mountains. This is significant not for the interest and engagement that it shows, but as evidence of David’s development of a more communicative disposition with respect to the domain of inquiry. Summary of Case 1
Let’s summarize what we have learned in this group’s case study. We have seen how two students established a set of norms of group work in data-rich inquiry with distinct characteristics: •
mutual support;
•
frequently shared or jointly-developed conceptions of the task;
•
co-direction of work strategies;
•
division of labor; and
•
joint, or uncontested, ownership of artifacts.
We have named this set of norms the “comfort zone,” to suggest the supportive environment it created for these students. We have seen that these norms afforded certain opportunities for reflection on complex data, especially through discussion of relationships between models and concepts, and reciprocal questioning and answering. We have also seen that these norms constrained certain opportunities for reflection in the data context, especially in cases of uncertainty and disagreement. We have seen how each of the students came to this group process with certain dispositions (evident in prior and early-on roles) which had kept them at the periphery of
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active engagement of data, and thus had constrained opportunities for reflection. LaTanya was a “Frustrated do-er” who tended to engage materials without engaging the data context of activity. David was a “Silent thinker” whose engagement of the data context was invisible to others and whose ideas did not find expression or development in the task context. We have seen how each developed new roles within and through their joint development of “comfort zone” norms. LaTanya became more of a “Questioner” – more disposed to link inquiry artifacts to their data-context referents, and more disposed to problematize tasks beyond their surface features. David became more of an “Explainer” – more disposed to make his confusion, his observations, and his explanations explicit to others. We have seen that these previously-silent ideas of his entered the realm of whole-class discourse. We have also seen that each of them developed new habits (in the task context) and new understandings of earth science (in the data context) that fit our model of reflection. That is, they both showed an increased ability and tendency to problematize elements of an inquiry situation, and establish connections with other elements of the task and data context to make meaning of them. Finally, we have seen that these students’ more-reflective roles and dispositions developed out of their identities and prior roles, rather than replacing them. Lessreflective and reflection-neutral dispositions did not disappear. Instead, these other aspects of identity and role (e.g. LaTanya’s focus on materials products of her work; David’s enjoyment of joking around) provided the basis for their development of more reflective roles and dispositions. What do these observations mean for our model of reflection in inquiry? And how can they inform the process of designing curriculum artifacts? These questions will be taken up in the discussion section. But one case is less than half as useful as two – we need some perspective on David and LaTanya’s experience. Next we examine another group of students whose norms, roles, and learning trajectory are markedly different from David’s and LaTanya’s.
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5.3) Case 2: the “Confrontation zone” Often the sight of two students arguing in class is cause for the teacher to step in and break things up. Some groups of students seem to argue all the time, either because of individuals’ confrontational dispositions or because of conflictual group dynamics – these groups often end up being re-grouped. Arguments in the classroom can be a big problem. On the other hand, argument can be a very productive kind of interaction under some circumstances. Reflective thinking often means not accepting other people’s ideas at face value, but looking for evidence to support assumptions. This can be a strength of argument as a form of discourse – it can force students to back up what they are saying. Rather than simply stating facts with a voice of authority, an argument can prompt a student to look closer at her own reasoning, question assumptions, and examine data. One design goal of the curriculum was to structure inquiry situations so that students would debate interpretations of data in this way. Of course there are many kinds of confrontations, and a fistfight over “who said what” is not the same thing as a debate over which position is better supported by data. However, my contention here is that a confrontational disposition can develop into a reflective disposition, and, in group-work with data, confrontation can prompt reflection. In the second case study, we look at a small group – Joel, Mario and Juan – in which confrontation was the dominant mode of interaction. We will see how the students sometimes entered a mode of work with data in which their arguing helped to problematize aspects of the inquiry situation, which otherwise would have remained nonproblematic. Who are Joel, Mario and Juan?
Joel is one of seven white non-immigrant students, and the only Jewish student in the class (though Jews are a large ethnic group in the community). Joel talks a lot during group-work, but he does not communicate casually – talk with his peers is usually loud, intense, and conflictual. His personality is loud and abrasive, and he infuriates his classmates on a daily basis. In any 10-minute period, it is common to hear Joel use the words “stupid,” “shut up,” or “bullshit.” Each of his six table-group partners had verbal conflict with him at least once during the course of the unit, including an ongoing argument between LaTanya and Joel about covering his mouth when he coughs.
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Joel is very outspoken with his opinions, both on-task and off-task. During group work he often alternates between rowdy goofing around with other boys, and loud arguments about the academic task at hand. Joel occasionally becomes very frustrated and upset, though he is often the instigator of conflict rather than a passive recipient. Joel has a learning disability, for which he is frequently pulled out of class for special services. This and other factors led to Joel being absent from many class activities. The teacher identified difficulty focusing, and difficulty working with others, as significant academic issues for him. Mario is from an Italian immigrant family. The teacher describes him as one of the top students academically in the class. He is very outspoken, opinionated, and sure of himself. In many whole-class discussions, Mario is the most frequent contributor. He often shouts out answers to the teacher’s questions, or frantically raises his hand and asks to be called on. In small group work, Mario will often state his solution for a task definitively, before others have thought it through. Mario carries a backpack with him that is literally bursting with papers and odds and ends. The teacher says that he desperately needs to organize his things – she challenged him to have an organized backpack by the end of winter break. He has a high level of energy and engagement in school work, but often cannot find his work, or has papers that are scrunched up and torn. His intellectual attitude might best be described as frantically engaged with ideas. Mario has many leadership qualities in the class – he is bold and confident, and academically successful. He also tends to be pushy and dominating, resulting in occasional conflicts with other students, sometimes including physical pushing. He also has a goofy streak that often resonates with those of the other boys, and during small group work it is not uncommon for Mario to be chasing someone around or joking loudly. Juan joined this table group a few weeks into the unit, and was teamed with Mario and Joel at that point. Juan is Mexican-American, and sometimes has brief social conversations in Spanish with the other two Mexican boys in the class. Juan is softspoken in group work – he occasionally contributes comments in whole-class discussions, but sometimes his quiet voice is hard to hear. Juan is a sensitive person, and seems to take great offense at Joel’s belligerence. Juan and Mario are close friends, and Juan seems most comfortable when the two of them are talking together, either socially or around an academic task. In group-work with Joel and
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Mario, Juan is often sidelined by the other two students’ high-energy talk. In larger group contexts such as table-group or whole-class discussions, Juan often stays around the periphery, looking for a chance to put in a comment. He seems interested in becoming more involved with the active discussions of the more advanced students, but often tentative about putting himself forward. Joel’s role in classroom activity early on: the “Gadfly”
Joel came to the Earth Structures unit with certain dispositions that provided valuable resources for reflection. One notable habit of his was to look for contradictory information – for any given “point” made by someone in discussion, Joel would often seem to look for a “counter-point,” or something that would disprove what had been said. This habit showed up in many different contexts, such as these contributions to wholeclass discussions: Hellene:
I think what happened is one plate crashed, then went down
Joel:
I don’t know if they could move that fast [98-10-23]
Here Joel immediately contradicts Hellene’s explanation, although he does not seem clear about exactly what she is saying – this is a characteristic kind of participation by him. In class discussions later in the unit his contrary comments become more grounded in data: Teacher:
We spent a lot of time plotting data on this map … Does anybody see – can anybody just make initial observations of any patterns that they see?
Hellene:
We [have], like the pattern, of, [earthquakes] usually on the border, like by the water
… Joel:
Um, not all of the earthquakes happen by the border, some happen just in the middle of the sea. [98-11-20]
Joel has found data points here to help him contradict Hellene’s observation. Similarly, later in the discussion Joel points to anomalous data to contradict a point made by Shelley: Shelley:
…
The question that you asked, what patterns we see? It happens in clusters or in groups -- not many happen alone by themselves
136 Joel:
Um, if you say a lot of earthquakes happen in the same areas, what about that one up, like, up there?
Teacher:
Here?
Joel:
Yeah, or the one around there? [98-11-20]
In this case Joel has singled out particular data points that do not fit into Shelley’s proposed data pattern (“it happens in clusters or groups”). Unlike a simple disagreement with an opinion, these observations of Joel’s require him to problematize particular points with respect to a pattern. This role of Joel’s might be described as “gadfly” – one who zips around “stinging” other group members, annoying them but also pointing out problems with their viewpoint. Joel’s comments usually served to critique ideas that were on the table, but rarely offered new ideas or built upon other ideas. This may be related to his difficulties focusing for extended periods of time – the teacher had a goal in this unit to move Joel toward better focus for longer time periods. It requires more extended focus to build up a possible theory than it does to discount one. Joel’s initial role:
§
Active participant in group talk
“Gadfly”
§
Contradicts other students’ ideas
§
Contributions are combative, not proposing positive suggestions
§
Difficulty focusing for long periods of time
One of the teacher’s goals for Joel before the Earth Structures unit was for him to learn to come to agreement with his group-mates, rather than just disagreeing. This goal is evident in this comment she makes to Joel a couple weeks before the unit begins: Teacher:
Joel ... this is your GROUP ... you have to AGREE ... if you don’t agree, you have to do it again! [98-10-08]
The teacher hoped to build Joel’s “stick-to-it-iveness,” as well as his social skills for working in a group. Joel’s comments quoted above suggest that his contrariness – often a source of bitter personal conflict – had the potential to be a resource for the reflective consideration of
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concepts and data, or just to be a source of interpersonal conflict. We will see how his role developed in the context of his group’s emerging norms of activity. Mario’s role in classroom activity early on: the “Answer Man”
Mario was an academic leader in the class, and a very active participant in classroom discourse. The nature of Mario’s leadership role in the class can be illustrated by looking at his participation in a characteristic discussion at the beginning of the unit. Out of a total of 155 student contributions during a lively whole-class discussion, Mario made 31 – more than twice the number of any other student, and 20% of all comments in a class of 27 students. Mario’s comments are often authoritative statements of the kind of information valued in most school discourse, as here when he provides a “text-book” answer to another student’s question: Sam:
Why DON’T we have earthquakes in Chicago?
Teacher:
Why don’t we have earthquakes in Chicago - see if we can come up with some possible explanations … Mario?
Mario:
We’re not like in the middle of two plates, like San Francisco and the rest of the Pacific coast is [98-10-23]
Mario has an impressive amount of this kind of text-book knowledge, and he proudly shows off what he knows. However, the teacher had a goal for Mario to push his understandings, and to recognize that much of his factual store of knowledge is what she calls a “house of cards” – trappings of knowledge without deep understanding. She often tried to get Mario to back up his authoritative statements with some kind of evidence, as when she interrupts him in this exchange: Teacher:
Why do you think [earthquakes] would be happening more often here in the United States than anywhere else in the world? … Mario?
Mario:
Because that would be clearly impossible in Asia and, right near the border of Europe and Asia, and all across the southern borders of Europe and Asia – like the Mediterranean and the Indian Ocean. Because those have – there’s even more plates happening there than in the western United States//
Teacher:
//How do you know that?//
Mario:
//Well, they’re more powerful anyways. Because the EuroAsia plate and the other plate, where they hit, there’s
138 like around – they hit – it seems like they’re hitting more, a lot more harder than the one across the American plate [98-11-20]
Here we see the teacher pushing Mario to give warrants for what he claims to know – she wants evidence for his explanations (“How do you know that?”). But he bulldozes ahead with his explanation, simply making it more detailed rather than providing any evidence. Mario’s initial role:
§
Very active participant in group and whole-class discourse
§
Provides authoritative answers, exhibiting his knowledge
§
Tries to dominate group strategy decisions
§
Rarely makes domain “facts” problematic
“Answer man”
In this way, Mario’s large stock of authoritative knowledge and dominating personality often stood in the way of his being reflective. His role, both in the whole class context and small group contexts, might be described as being the “Answer Man” – the one who could come up with the “right” answer, quickest. He did not tend to pull back from proclaiming facts long enough to question the validity of those facts. Juan’s role in classroom activity early on: the “Peripheral Partner”
We don’t have as much classroom data to draw on in characterizing Juan’s early patterns of participation, as he was not initially a member of the focus table group. However, the data we have suggest an interested but tentative pattern of participation in group activity. Juan often seems to be following whole-class science discussions closely, raising his hand at times, occasionally contributing an idea. These contributions are usually very quiet, sometimes going unnoticed. Juan sometimes engages in extended one-on-one conversations with Mario about the domain concepts and the data. In these one-on-one interactions, Juan usually is a follower, going along with what Mario is saying or repeating his words. Juan did not work one-on-one with Joel for any extended period of time, as their interactions tend to devolve into horseplay or arguments, with Joel yelling and Juan becoming frustrated. Juan often has trouble staying on top of his “stuff.” His written work often remains halffinished or gets lost, and, like Mario, he seems to have trouble keeping his folders and
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backpack organized. This sometimes is a source of frustration, as he seems to want to be part of the debates and discussions of other students, but he can’t quite manage it. In the teacher’s words, “He’s got it up here [in his head] to engage in those conversations, but his disorganization holds him back.” Juan’s initial role:
§
Tentative contributions to group and whole-class process
§
More comfortable one-on-one
§
Has trouble making his ideas heard by others, unlikely to argue
“Peripheral partner”
Juan’s role might be summed up as “peripheral partner.” He wants to be more centrally involved, but he often remains on the outskirts of the group’s activity. Developing group norms with data: the “Confrontation zone”
During the unit, this group worked very hard at examining the complex data that was made available to them. In all, they probably looked at more data images on computer screens than any other group, led by Mario. All three showed signs of making progress toward a more reflective stance toward data and domain concepts as the unit went on. A major cause of this progress seemed to be their tendency to argue with each other. Reflective comments in separate spaces
Unlike David and LaTanya, who are marginalized in different ways from group discussions about data at the outset of the unit, Mario and Joel are among the most vocal students in the class. Even though Joel is often unfocused and abrasive, he participates loudly in his group. Mario, as we have seen, often dominates group discussion. Their vocal dispositions, however, did not always mean that they were communicating! From the first Focus Activity, Plotting Current Earthquakes, both Mario and Joel are generating lots of observations about the big datasets they encounter. (Juan has not joined the group at this point.) They both seem to love looking at, and thinking about, information. Note their excited and reflective reactions in the first 20 seconds after being handed their data list for plotting earthquakes (an episode we have looked at earlier): [teacher hands list to Joel] Mario:
We get the Central US!?
[smiling around table]
140 Joel:
[reading]
Central USA.
[Mario and Joel look over the list of earthquake data] Joel:
‘96.
And the latest is right here [pointing]
Mario:
Oh my god! [pointing at data list] … All that is in 2 years. [to whole table, smiling] All that is in 2 years!
Marie:
That is pathetic! Wait, when’s a recent one? over to look at list]
Mario:
8/23! … August 23rd!
[leaning
… Joel:
The biggest was 4.3!
Mario:
But when they come, they come big! [98-10-26]
Mario and Joel have wasted no time in problematizing the data. Joel is handed the data list, and he right away starts characterizing particular data points in relation to the whole data set: he looks for the latest one, then the biggest one (see Figure 5.21). They were not assigned to figure these data relationships out, but Joel adopts this questioning perspective, making data points problematic on his own.
Figure 5.21. Joel problematizes data points in terms of their relation to the data set as a whole.
Mario shows surprise at the number of earthquakes on their list over a two-year time span (“Oh my god! … All that is in 2 years!”). This observation makes the amount of data problematic, which again involves stepping back from the immediate plotting task to consider the data from another perspective – apparently comparing this region’s amount of data with other regions they have been looking at as a class. Mario further problematizes patterns in the data when Joel says the biggest earthquake is a 4.3. He generalizes a rule to account for the small amount of data he and Marie observed (“That is pathetic!”), combined with Joel’s observation of the largest magnitude (“The biggest was 4.3!”) – Mario’s rule for his region is, “But when they come, they
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come big!” He is clearly connecting the information they have about particular earthquake events, to the nature of the part of the world they have data for (see Figure 5.22). In this group, only Mario and Marie make these kinds of explicit connections to actual geographic regions during this activity.
Figure 5.22. Mario problematizes data patterns, relating them to point values and real-world referents.
This tendency of both Mario and Joel to actively problematize data – generating observations, questions, and explanations, even outside the requirements of the assigned task – is evident in many such episodes, from the beginning of the unit on. This would suggest that their group should benefit a lot from these reflections – right? But they didn’t listen to each other
However, there were other aspects of their dispositions that made it difficult for Joel and Mario to use their observations to actually figure anything out! They each distanced themselves from the group in different ways. Mario often showed signs of the classic performance-goal disposition of many top-achieving students (Dweck 1986) – the need to know most, or to be right. Joel showed signs of needing to disagree with almost anyone. This combination meant that their ideas often went right past each other. For example, in this episode, Mario, Joel and Marie debate the best strategy for choosing data points from their list to plot. Neither Mario nor Joel seems to notice what the other one says, but just shouts his own idea back at the other. Contrast this with Marie, who eventually weighs the alternatives thoughtfully and sides with Joel: Marie:
[to Joel]
Here, check ‘em off as you go along
Joel:
No. Come on, let’s do the highest, let’s do the highest one we got – let’s do 4.3
Mario:
Let’s do all of em
Joel:
Shut up, let’s do the highest one
Mario:
We’re supposed to do, like, at least a couple for each state
142 Joel:
Yo, Mario, let’s do the highest one we got
… Joel:
Shut up and do this one!
… Joel:
This is the highest one, we should at least put that
… Joel:
Marie! This is the highest latitude, we should at least do this one
Mario:
You can’t do every one! though
Joel:
Let’s do the highest magnitude we have!
Mario:
Do like a couple in each state
She said not to do every one
… Marie:
[to Joel, looking at data list] Where’s the magnitude? – This is it?
… Marie:
[leans across table towards Joel] The highest one on this one is a 4.3 – [goes over by Joel to look closely at list] … Lemme see, what’s the highest …?
Joel:
Arkansas, the second one … Strawberry, Arkansas
Marie:
[coming back to group] OK, we gotta do, uh – OK, Joel is RIGHT!
Mario:
No, man, Joel is WEIRD [98-10-26]
Despite 16 comments exchanged here among these three students regarding which points to plot, neither Mario nor Joel seems to have heard any ideas but his own. Rather than figure out what Joel and Marie have agreed upon, Mario just makes fun of Joel. The strategy of plotting the highest-magnitude earthquakes is lost in the shuffle, and the group finishes the activity without a clear idea of which points they are choosing or why. Each student in this episode is problematizing the strategy in connection with their conceptions of the task, but their reflections do not find their way into the group’s discourse (see Figure 5.23). The group’s activity is buzzing with words and ideas related to the task and the domain, but Mario and Joel cannot focus together on relating the taskstrategy decisions to the data context.
143
Figure 5.23. Joel and Mario’s reflections on strategies do not come together in the group’s discourse. Joel begins to push Mario: The Case of the “Big Old Gap”
But as the data become more complex in Focus Activity 2, Mapping the Plates, Joel’s challenges to Mario begin to slow him down. Mario begins the activity by stating the answer (the outline of their plate) definitively, but he is instantly challenged by Joel: Mario:
[to his group] THIS is the plate.
… Joel:
The plate boundary is right over HERE, Mario!
Mario:
Yeah, but it goes up here
Joel:
But it’s over here too – it goes like this!
Mario:
That’s what I’m saying!
[Mario draws line, Joel and Juan watch closely] Joel:
Go all the way around
Mario:
I put it like all of this
Joel:
That’s it
Mario:
What about down here?
Juan:
{inaudible, pointing}
Joel:
No, but it stops -- see right here it stops – No no no -right here it stops! [lifting Mario’s pen from the map] – and then it starts up again!
Mario:
I know!
Joel:
But it’s sort of right in the middle
That’s one plate too!
144 [98-11-25]
Joel here has stopped Mario from imposing a simplified conception of the task on the group. Mario becomes more tentative as Joel challenges him, though he tries to maintain his authoritative posture (“That’s what I’m saying!” … “I know!”). But Joel has noticed something in the data that Mario had missed: an area of Mario’s plate boundary line where there is no earthquake data at all (“See right here it stops … and then it starts up again!”). When Joel says that the plate can’t be the shape Mario has drawn, Mario retreats from the data and uses his domain knowledge to defend himself: Mario:
Why? Plates are huge, man! the whole Euro-Asia!
There’s a plate that takes up
Joel:
Mario, look – this is where it really starts, see it goes up – and look what happens! Look what happens! It starts to drop!
[Mario and Joel and Juan huddle over the map talking] Mario:
There’s that big old gap! there
There’s a big old hole right [98-11-25]
Mario’s reference to a “big old gap” represents the first time in the unit that he changes his position as a result of a confrontation – Joel has convinced him that there is a “big old gap” in the data. This problematic observation brings the three group members into close examination of the data for some time.
Figure 5.24.. Joel and Mario jointly problematize a data pattern and make reflective connections.
This represents a new degree of intersubjectivity, or joint focus, on the interpretation of data. Rather than each pursuing his own idea, the debate brings them to a point at which the same pattern of data is problematic for both of them (see Figure 5.24), prompting connections to concepts from the domain (“What about down here? That’s one plate too!”), real-world places (“There’s a plate that takes up the whole Euro-Asia!”), and their
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strategy for completing the task (“Go all the way around” – “What about down here?”). Joel’s argument has made Mario look again at the data, and Mario’s strong-willed argument has forced Joel to make his disagreement explicit. Problematizing is shared across groups
This shared act of problematizing the data pattern is shared not only between these students, but then with other students as well. Joel’s “big old gap” observation is carried by Mario over to David and LaTanya’s group later in the period, when Mario goes to talk with David. He states authoritatively that David’s plate is the same as his own group’s plate, and then he points to the area that Joel has problematized for him: Mario:
[pointing to David’s side of map] What the heck is this? Is this the bottomless pit or something?
David:
I know!
Mario:
Right here it’s a bottomless pit!
David:
Put a question mark!
Mario:
[joking tone] “They say no one has ever lived here…”
There’s like nothing here!
[laughs]
[98-11-25]
Juan joins in, and writes “What is this?” on David and LaTanya’s plastic, pointing to the “big old gap.” The argument about the data becomes a shared process of problematizing – all five students at the table end up looking at and talking about this data pattern. When LaTanya complains about Juan writing on her plastic, David jumps in to explain about the “bottomless pit.” In this way, Juan, David and LaTanya all become secondary beneficiaries of Joel and Mario’s argument about the data (although LaTanya rejects it). Constructive confrontation became their main mode of work
For most of Focus Activities 2 and 3 – mapping the plates, and identifying plate boundaries – this mode of confrontation between Joel and Mario was common. Sometimes it resulted in shared observations, as in the episode above, while other times it did not go beyond simple disagreement or bickering. But in each case, Joel was forced to draw out his observations in order to challenge Mario, and Mario was forced to reevaluate and make his understandings explicit in order to counter Joel.
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Group norms:
•
mutual challenging rather than support
“Confrontation zone”
•
hotly debated conceptions of the task
•
competition for deciding on group strategies
•
difficulty with division of labor
•
contested ownership of inquiry artifacts.
To illustrate the kind of confrontational discourse that was the norm for this group’s work with data, we next examine one five-minute episode of work at the computer from Focus Activity 2 (transcribed below in Table 6), as the group tries to determine the exact shape of their plate. They are using the computer software to consult more data than they have on the paper maps. For each comment in the discussion, I have suggested a role the comment plays in an ongoing argumentative interaction, mainly between Mario and Joel, but also including Juan toward the end. What is remarkable here is the consistent pattern of confrontation prompting explicit discussion of observations and explanations. The debate begins about whether an image on the computer is showing them the earthquake data that they need to support their plate boundary prediction in one area. Table 6: A five-minute small-group discussion in the “Confrontation zone.” Student
comment
Confrontation zone implication
Joel:
I think this is right
STATES OPINION
Mario:
No, we messed up somewhere, it didn’t show us the screen. Or maybe it did, but it didn’t look like it, it looked like it was just showing us this – right there
CHALLENGES EXPLAINS DISAGREEMENT
[Mario clicks around, zooms in on Caribbean] Mario:
Hang on – yeah, this is Mexico right here. No, this is Florida right there, and this is Mexico right here.
MAKES OBSERVATION EXPLICIT
[Joel points to earthquake data button]
SUGGESTS DATA
[Mario clicks it, gets dialog, enters query]
MAKES DATA DECISION
Mario:
There’s gonna be a lot, watch.
MAKES EXPLICIT PREDICTION
Joel:
{inaudible}
147 Mario:
It didn’t show it – I know. didn’t show
[Mario captures image in Progress
It just
Portfolio]
Mario:
OK now, one more
MAKES STRATEGY DECISION
Joel:
Why is {inaudible} in Florida?
ASKS FOR EXPLANATION
Mario:
It’s on the other side of the world – the other side of the U.S.
AUTHORITATIVE ANSWER
Joel:
You mean like California?
CLARIFYING QUESTION
Mario:
That’s the other plate though. That’s not our plate. They’re doing the plate that’s from – right along here. Florida’s on the plate that’s from here to here.
CORRECTION
Joel:
But ours is right around California, it’s right around the San Andreas fault which is in California
CHALLENGES
Mario:
You said Florida though
COUNTER-ARGUES
Joel:
Let’s check out California
SUGGESTS NEW STRATEGY
Mario:
We know what California’s like, we know there’s a whole bunch there, so we can’t start with that one
CHALLENGES STRATEGY
Joel:
Yeah, I know
CONCEDES THE POINT
Mario:
We gotta go down here – like we did yesterday. But this time closer to South America
MAKES POINT MORE EXPLICIT
[pointing]
MAKES OBSERVATION
MAKES POINT MORE EXPLICIT
SUGGESTION, WITH EXPLICIT REASON
… Mario:
South America.
{…}
[EQ dialog comes up, A starts clicking]
DECIDES STRATEGY
… Joel:
[peering over] I don’t think we got enough information
STATES OPINION
Mario:
It’s all the information there is!
CHALLENGES
Joel:
[points west] way
COUNTER-ARGUES
Mario:
It does go that way, that’s why you have it there. … I gotta go even deeper.
Mario, it might go this
[Mario calls up EQ dialog, types in a value]
MAKES POINT MORE EXPLICIT DECIDES STRATEGY
148 [Juan comes over, looks at Mario’s query] Juan:
… 1000?!
The minimum!
The maximum 1000.
Mario:
What’s the minimum on that last one? I have to see the scale first. I think it might be 800. Oh, that’s the magnitude! Wait a minute. Good thing I didn’t do it there, I did it on the wrong one.
QUESTIONS STRATEGY
Mario:
Let me do it then – no, I just won’t put a maximum. You don’t have to put a maximum – see, you can’t put a maximum unless, um
MAKES STRATEGY EXPLICIT
Juan:
See I told you, you didn’t put 1,000. Ooooh, I told you, I told you… 1,000
COUNTER-POINT
Mario:
I want to map it now guys. we do here?
REQUESTS ADVICE
Juan:
Make the color more dark — more whiter, like white
CHALLENGES STRATEGY
…
Hey, what do
SUGGESTS STRATEGY
[98-12-03]
This extended example shows the way confrontation pushed this group toward more reflective work with data. They debate strategies for the investigation (“we know there’s a whole bunch there, so we can’t start with that one”); strategies for querying the database (“See I told you, you didn’t put 1,000”); and interpretations of data patterns (“Mario, it might go this way!”). Though Mario maintains primary control of the investigation, both Joel and Juan are actively engaged in a group process of figuring out the data. Difficulty consolidating understandings
Though Joel, Juan and Mario did benefit from this confrontational mode of work during the investigation, they had trouble consolidating their reflective observations and explanations into a coherent set of understandings toward the end of the unit. As they reached Focus Activity 4, Preparing a Presentation, they began to encounter difficulties. Unlike LaTanya and David – who spent extended periods of time during this phase coming up with ideas for making models of plates – Mario, Joel and Juan never established a mode of work in which they could reflect back on what they knew. Their confrontational mode got in the way of making sense of what they had done.
149
For example, during a total of nearly 50 minutes spent at the computer during one day, they were never able to actually talk about what they would do for their presentation. Examples of their talk during this period show the difficulty they have in co-constructing a story: Joel:
Mario, come on … Remember that presentation thing … ? should start on that
Mario:
We don’t even know what we’re gonna talk about yet
Joel:
Start writing.
We
[Mario comes over and types] Joel:
Let me do one thing. everything on here …
Al, stop. … I wanna arrange [98-12-17]
Joel has no idea about how to proceed, but doesn’t know how to discuss ideas for the presentation with Mario. Mario simply sits down and starts writing out his own ideas. Later, after a break, Joel tries to get involved again: Joel:
Should we start out by putting our names, then the date?
… Joel:
Don’t put a comma!
… Mario:
This ain’t a friggin’ sentence man! [98-12-17]
Their debate never moves out of this superficial bickering. After about 30 minutes, Mario has been typing alone for some time. He is asked to make sure he is working together with his group: JR:
Mario, it’s a group project, make sure the others know what’s you’re doing
Mario:
[to Juan]
Joel:
Let me see what you’ve got so far when you’re typing – I wanna read it.
Juan:
[at keyboard]
Mario:
Put “We knew – ”
Juan:
OK, what else?
Do you wanna type?
“A clear line of earthquakes” – what?
What else?
[Joel and Mario start to argue about sports] Juan:
What else?
150 [98-12-17]
Juan’s efforts to get down some of Mario’s ideas are frustrated by the argument, and the presentation is never completed. The only written passage in their final Progress Portfolio document is a paragraph written by Mario explaining general concepts: In this presentation we will be discussing about how our earth's crust works. The crust is the layer of the earth that we live on. The crust is made up of many plates (parts) and were doing a rather large plate called the Eurasian plate. We discovered odd land formations that you won't find in or around Chicago. What we mainly did was find naturual disasters and try to predict where these plates are. We did this because earthquakes and volcanoes are usually caused from plates rubbing against each other. Where there was a clear line of earthquakes, we knew this was a plate border. [from final Progress Portfolio document]
There is not much evidence in their presentation of all the painstaking data analysis they have done during the unit. The same confrontational mode of interaction that got them deep into the data, also made it difficult for them to collectively make sense of those experiences. Mario and Juan consolidated understandings in a “comfort zone”
Without Joel, however, Mario and Juan had the benefit of sharing a comfort zone similar to LaTanya and David’s, in which they could re-visit concepts and data interpretations. This proved to be an important interactive space for consolidating what they were learning from the work with data. In an example from Focus Activity 3, Mario and Juan try to make sense of the patterns of earthquakes around their plate: Juan:
[reads from his science journal] BUCK-ling zone. ling. BUCK-ling.
BUCK-
Mario:
[pointing to a map of their plate with data] Do you think this is a buckling zone? [Juan looks at map] This one right here. Or is this the one that moves – transform zone?
Juan:
[looks at his science journal] What is a transform zone? Oh yeah, it’s in front of each other [moves hands in buckling motion] – oh no//
Mario:
//No, it’s just like this
[they both slide hands past each other for transform motion] Mario:
Ours has buckling zone, the rift zone – transform zone
Juan:
They move apart like that [makes rift hand motion]
151 Mario:
[looks at data map again] This might be a rift zone here. [pause] What’s the volcano one?
[Mario looks through Juan’s science journal] Juan:
Volcanoes are – it’s, ummm, subduction zone. [reads from his journal] It’s when an oceanic plate – goes under the continental plate
[they read together from Juan’s journal] Mario:
And buckling is – [looks at data map] – I think it’s a subduction zone
This discussion shows fluid movement among three elements of the data context: models representing data and concepts (the picture of their plate which they point at; hand motions), patterns of data (“This one right here” – “What’s the volcano one?”), and several domain concepts (“They move apart like that” – “It’s when an oceanic plate goes under the continental plate”). The models, patterns and concepts are discussed in a way that binds them tightly together (see Figure 5.25).
Figure 5.25. Mario and Juan strengthen their data-context connections within “Comfort zone” norms.
Mario’s tone in these “comfort zone” discussions with Juan is very different from his tone in other classroom contexts. Rather than being authoritative and commanding, Mario asks Juan questions (“Do you think this is a buckling zone?”) and looks in Juan’s journal to figure things out. Mario’s tone is more inquisitive and tentative than in other contexts. Mario has opportunities for a different kind of reflective talk in this zone that are not available to him in the more common “confrontation zone.” Juan also benefits from this space: he engages in sustained discussions with Mario, whereas in other contexts he usually becomes quiet and peripheral. Joel, however, did not benefit from Mario and Juan’s comfort zone. When he joined them in this mode of work at the computer, he often tried to bully the interaction to go his way, rather than listening and watching what they were doing. While his participation in group arguments had become more focused and productive, he had not developed the
152
skills of comfortable discussion in the small group. He was neither a primary nor a secondary beneficiary of Mario and Juan’s comfort-zone realizations. Learning outcomes: changes in roles, dispositions and understandings
We have seen changes in Mario and Joel’s mode of group work that developed during the unit – Mario’s increasing willingness to question his own assumptions, and Joel’s increasing disposition to listen to someone else. But we have also seen that these changes did not stay with them once and for all. Bickering conflict remained as a habit, and reflections around data did not extend to other phases of inquiry activity. What kinds of learning were afforded by the Confrontation zone fore these students? Joel’s beginnings of inquiry-focused dialog in the group
Joel’s learning from the Earth Structures unit was a mixed bag. Joel showed great frustration during the individual post-interview (there are several likely reasons for this frustration, not all of them related to his experience in the unit). He seemed to feel that he had not learned what he was supposed to learn during the unit, and made several explanations for this – having missed several days, having been called out of class frequently. Inconsistent connections in the data context
His responses in the post interview suggest that he picked up a number of explanations for earth science phenomena, but he did not make some crucial connections to tie together models, concepts, and data. He has expanded some on a basic domain explanation for earthquakes: JR:
Can you explain what an earthquake is?
PRE-INTERVIEW ANSWER: Joel:
Um, let’s see. It’s partially a fault, in the earth’s crust, umm – I --- [laughs] I don’t remember much about it
POST-INTERVIEW ANSWER: Joel:
Underground shockwaves, I think. Where two plates collide, and make a volcano, shoot up a lot of lava
He has connected earthquakes with plate motion, and plate motion with volcanic eruptions. Joel also shows that he remembers some of the explanations encountered during the unit, and can connect some of them to places on a map:
153 Joel:
This is the highest mountains in the world, it has to be higher.
JR:
OK.
Joel:
No. Mt. Everest is higher, isn’t it. it right here? Or there?
So these are the highest? [Rockies] Which is in – isn’t
… JR:
Can you tell me any differences between those two mountain ranges?
Joel:
I’m not positive which one grows, but I think this one grows, or this one grows [Himalayas] but this one doesn’t.
JR:
And why do you think so?
Joel:
Plates are still pushing it up. [post-interview]
Here we see Joel’s tentativeness about his understandings, his partial ability to connect places in the world with domain explanations, and some connection between these and places on maps. But he has also held on to some misconceptions that he had at the beginning of the unit – that earthquakes happen where the weather is hot; that the ocean floor is deepest in the middle of the ocean and shallower by land; and that earthquakes are connected with tornadoes and hurricanes. These false assumptions are directly contradicted by Joel’s other comments in this same interview, and by the data he looks at, but he has not developed a comprehensive domain understanding that enables him to move beyond them. Tentative steps from “Gadfly” to “Strategy Suggester”
However, a pre-post group activity that we conducted, in which students do an extended investigation using multiple complex data-sets, tells more of the mixed story of Joel’s learning in this unit. Unlike the pre-unit group activity, the post-unit session shows Joel using some adaptive group-work approaches. He still contradicts his companions repeatedly, but he also shows signs that he is listening to what they say. He repeats back some of their observations later (“You said this was desert up here, right?”), and he uses some of their arguments as his own explanations for data (“I’m gonna go with Pasadena, because it’s around the desert ”). More importantly, Joel proposes specific strategies for his group to use in organizing data and completing their task. He initiates a color-coding scheme for marking areas on maps,
154
and he suggests ways to order their maps as they work (“Let’s line up the maps that we’re gonna need in order, so we don’t need to keep looking back and forth”). He also proposes a system for ruling out particular data-sets in their investigation (“It’s elimination! Let’s play a little game!”). This kind of constructive participation is new for Joel, and is not seen in the pre-unit group interview at all. However, Joel’s antagonistic style prevents these efforts from succeeding. He does more yelling and contradicting than anything else, and he ends up working alone, while David and Mario pursue the investigation in their own way (“You keep doing that, I’ll keep doing my elimination process”). In the end, he is unable to put forward any solutions for the task which account for the data he has used, while David and Mario have constructed data-based solutions and explanations together. Joel still has difficulty using his arguing strategically, and building understandings together with others. Mario’s development of self-questioning and communication around data
As described above, Mario started the unit with a huge amount of domain understanding, including a conception of “plates,” an idea of where plate boundaries might be, and a rough understanding of the relation of earthquakes to plate boundaries. His learning during the unit involved both expanding on his extensive knowledge, and becoming more able and willing to question his understandings. For example, Mario knew before the unit began that the Himalayas were the tallest mountains in the world, and that the Himalayas were believed to have formed from a collision between the Indian sub-continent and the rest of Asia. This understanding is expanded in the post-interview to include the concept of this process as “buckling” of two plates at a boundary (“A buckling zone is plates ramming into each other”), also understood in terms of data patterns as evidence (“You look for mountain ranges, scattered volcanoes and earthquakes”). Mario is able to use this understanding not only to refine his earlier understandings, but to pose questions for himself about other areas. Note his thinking in the post-interview discussion of mountain formation: JR:
How did the mountains get to be so high?
Mario:
Mostly from buckling zones, you’ve got the plates ramming into each other.
JR:
Can you show me an example of that?
Mario:
India ramming into Asia, the Himalayas. [Looks around the world map] I know this one [the Appalachians] might be
155 one ... I think the Rockies are [a buckling zone], but it just happened more inland . [pause] I just don’t know what hit em to cause that
Mario here willingly points to examples that highlight his lack of certainty, and in further discussion of these examples, he challenges himself by pushing his understanding of the “buckling” process: JR:
What information do you think you might check to find out if they’re buckling zones?
Mario:
Ummm – I’d look for mountain ranges, that kind of knocks that off. It would have like a plate border, or two plates near each other – two plates hitting each other form a buckling zone. But it also could just be one plate.
This idea that buckling could “just be one plate” – i.e. could happen far from a plate boundary – is necessary for Mario to explain how the Rockies and the Appalachians could be the result of buckling. Mario here is engaging more sophisticated understandings of plate tectonics than other students in the class. More importantly, he is pushing his attempts to explain data beyond what he can now comfortably explain (“India ramming into Asia”), toward less clear and more challenging concepts. Mario is also able to identify gaps between his predictions, and subsequent observations from data in the post interview. Like many students, he is at a loss to explain the centralAfrican volcano pattern (“I’m kind of surprised right here! Why are there none really down here, then some right here?”). When asked what might explain the anomalous pattern, he is able to consider more than one possible explanation (“Saudi Arabia might be hitting it … or this might be moving this way”). These reflective patterns are not altogether new for Mario, whose inquisitiveness and self-challenging existed before the unit. But as the teacher had hoped, he was able to question some of his more comfortable assumptions, problematizing not only data but also his grasp of particular explanatory concepts. Mario’s dispositional learning included an important new pattern of engagement in group work, as we have seen above – co-constructing observations and explanations with his classmates (rather than for them), and allowing others’ observations to help him question his own understandings. Mario was able to shift his role from having to be the “Answer Man” toward a more inquisitive “Co-questioner” role. This shift contributed to his willingness to exhibit gaps in his knowledge. It also was marked by a less bossy tone in
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the small-group post-interview, in which he and David shared an extended process of suggesting and critiquing explanations of data patterns. Juan’s unknown learning in the unit
Since Juan was not part of our focus group for part of the unit, we did not gather enough data to accurately characterize his learning. He was not interviewed individually or in the group, and his work products were not collected. This is unfortunate, since his role is an important one for understanding learning in the “confrontation zone.” Juan was clearly a secondary beneficiary of the group’s arguments, and it would be valuable to have a clear picture of what kinds of learning take place for students in this position. Also, Juan was someone who clearly was more productive in the “comfort zone,” as we saw in his one-on-one work with Mario. It would be valuable to know how the confrontation zone impacted his development of roles and understandings. Juan seemed to become more confident in his ability to engage in reflective discussions through his comfort zone with Mario. He clearly benefited secondarily from Mario’s learning with Joel. But the confrontation zone seemed to prevent him from developing more ownership of the inquiry, and developing the organizational and participatory skills that he needed to become more centrally involved. Summary of Case 2
Let’s summarize what we have learned in this group’s case study. We have seen the development of a different set of norms of group work from Case 1, marked by: •
mutual challenging rather than support;
•
hotly debated conceptions of the task;
•
competition for deciding on group strategies;
•
difficulty with division of labor; and
•
contested ownership of inquiry artifacts.
We have named this the “confrontation zone,” for obvious reasons. The picture in Case 2 provides a sharp contrast with Case 1. Still, we have seen that these norms also afforded certain opportunities for reflection on complex data, especially through debate over
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strategies, and challenging of observations – both of which prompted increased reference to data and explicit explanation. We have also seen that these norms constrained reflection, particularly through their limiting of co-creation of artifacts to record students’ reflective connections in the data context. We have seen how each student came to this group with different dispositions which included valuable resources for reflection (e.g. Mario’s domain knowledge; Joel’s disposition to challenge; and both boys’ verbosity), but also certain impediments to reflection. Joel was a “Gadfly” who often disagreed, but did not stay focused on an issue long enough to develop connections or propose constructive strategies. Mario was an “Answer man” who often looked for the quickest way to show off his authoritative knowledge, and was not interested in being shown up or being wrong. Juan was a “Peripheral partner,” thinking independently but not finding ways to become centrally involved in group inquiry. We have seen how Mario and Joel began to develop new roles within and through their joint development of productive “confrontation zone” norms. Mario became more of a “Co-questioner,” listening more closely to his challengers, and more disposed to look deeply into data before proclaiming an “answer.” Joel made significant steps toward becoming a “Co-strategizer,” not just criticizing but also suggesting coherent approaches for group work. Both became more willing to develop a conception of task and strategies through discussion rather than through forceful proclamation. Juan’s development is less well-known, due to the lack of data. He seemed to stay peripheral in many ways toward the end of the unit. However, within his comfort zone with Mario he seemed to grow into a more central role, benefiting from Mario’s “Coquestioner” role and clearly stating his ideas. This did not seem to carry over to the 3student group, nor to other class activity contexts. We have seen how each of these students’ development of new roles and dispositions relate to our model of reflection in three contexts – an increased disposition to view inquiry artifacts as problematic rather than settled (Mario); an increased orderliness to the flow of suggestions and connection of perspectives over time (Joel); and an increased likelihood to make use of the small-group activity context to explore these relationships. We have also seen more limitations in the development of new data-context understandings with this group. We have surmised that the difficulties they had in the final phase of the unit (Presentation preparation) may have inhibited the process of retracing reflective connections, which clearly played an important role in Case 1.
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Finally, we have seen again how the development of more reflective roles and dispositions, and the effective use of reflection to develop domain understandings, does not grow in opposition to prior identities and roles. Rather, we have seen how the “confrontation zone” norms provided a fertile ground for the movement of at least two group members’ prior dispositions toward more reflective versions of themselves. Nonreflective and reflection-neutral dispositions (e.g. Joel’s obstinacy; Mario’s dominance of strategizing) can develop in parallel, or alternate with their more-reflective counterparts. What do these contrasting cases tell us about the development of reflective inquiry dispositions? That is the question taken up in the next section of the data analysis.
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5.4) Validity of the constructs: other groups as reference points We have seen two groups’ development of contrasting patterns of inquiry activity with complex data – the “Comfort zone” and the “Confrontation zone.” We have seen how these patterns shaped individual students’ development of reflective roles, and the kinds of domain learning that were afforded by these roles. This discussion has demonstrated the interplay between the data context, the task context, and the role context shaping opportunities for reflection, and shaping the development of more reflective dispositions. One take-home from this discussion is that group norms matter. As educators we must look at the formation of groups as important design work, and we must recognize opportunities to leverage the existing dispositions of students to promote the development of new group norms and new individual roles. Different students will be prepared to develop reflective roles in different ways – depending upon their existing roles and identities in the role context, and depending upon their interactions with others in the task context. Having a picture of many different paths students might take toward more reflective dispositions – as we have seen in the data analysis – can provide the beginnings of a helpful “road map” of possible paths of reflective development to look for. But it is important to make sure that the norms and patterns of development here are not completely idiosyncratic, and unique to the individuals and circumstances described in the case studies. If Mario is the only student who is likely to move from an “Answer Man” role to a more reflective “Co-questioner” role through a series of confrontational interactions with only Joel, then we do not have a road map, but only a couple of interesting stories. Generality of observed patterns of group norms
This tightly-focused study cannot address the question of how general our categories might be for other groups, or suggest how many different kinds of group norms there might be. But we can show that the norms of group work with complex data identified in our case studies were not unique to these two groups. In other classrooms we find other groups interacting in similar patterns, with some similar outcomes, and some interesting differences. I will briefly overview some of these cases, to establish the relevance of our observations so far.
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Other examples of the “Comfort zone”
We have defined the comfort zone as a mode of group-work with data having the following characteristics: •
mutual support;
•
frequently shared or jointly-developed conceptions of the task;
•
co-direction of work strategies;
•
division of labor; and
•
joint, or uncontested, ownership of artifacts.
It is first important to point out that this set of group characteristics was not a foregone conclusion for either David’s or LaTanya’s individual patterns of participation. Both had been in groups earlier in the year in which they had participated very differently. LaTanya had been in confrontational groups which had not been very productive for her learning. David had been a quiet follower and off-task joker, even in early groupings during this unit. Thus the comfort zone was not simply an extension of either of their personalities. But neither was it unique to the two of them as a pair. There was evidence in other groups, and in other classes, of a similar comfort zone. We have already seen one other example of students working in the “comfort zone” – Mario and Juan. In their one-onone collaboration, these two followed patterns of interaction that meet the criteria for a comfort zone. Interestingly, they often shared David and LaTanya’s focus on models in their one-on-one discussions, though they also spent more time reviewing data. Mario and Juan are an interesting comparison case to David and LaTanya, in that (1) they were already close friends before the unit, whereas David and LaTanya were not, and (2) they are a same-gender pair. These differences show that the comfort zone can be formed across groups that differ at least in these ways. A second comparison case provides another important axis of difference. In the InterAmerican 6th grade classroom, Aaron and Troy formed another small group that worked in a comfort zone with complex data. Like both of the comfort-zone groups mentioned so far, they are students from different ethnic backgrounds (Aaron is white, Troy is African American). But an important difference from David and LaTanya is the academic make-up of this pair. Rather than both being “middle kids,” Troy and Aaron identified them as representing the lowest and highest academic levels in the class, respectively. Is the comfort zone a mode of interaction that can only develop when
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students are of similar academic levels? This comparison case shows that this is not the case. In the episode below, we see Aaron and Troy sharing observations, conceptions of the task, and especially a great enthusiasm for finding what’s in the data. This is during Focus Activity 1, and Aaron and Troy have decided to work together on finding more earthquake data for their chosen region: mid-northern Africa. Comments that suggest the “comfort zone” mode are identified in the right-hand column of Table 7. Table 7: Evidence of Troy and Aaron’s Comfort Zone Student
discourse
Comfort
Aaron:
All right!
Troy:
Af-ree-ka!
Aaron:
[looking at Africa data list on computer] They have a lot of big ones! Yay!! … a big one!
[Aaron looks for magnitude 7 earthquakes – then decides to look for 6’s and 7’s. Troy goes to get red stickers – the color they are using for magnitudes 6 and above]
zone
evidence
DIVISION OF LABOR
… Troy:
[running over]
I got it, I got it!
Aaron:
OK, we need to highlight 6’s right here
Troy:
Alright, OK. … Let’s do the 6’s
Aaron:
OK, that’s a … 7 right there. there …
Troy:
All them all right there is 6’s There go a 6 right there, there right there, there go a 7 right there go a 7 right there, there right there, there go a 7 right there go a 8!! That’s a 8!
Aaron:
So there is an 8 here!
SHARED CONCEPTION OF TASK
“ 7 right
CO-DIRECTED STRATEGIES
and 7’s. go a 7 there, go a 7 there,
“
JOINTLY-DEVELOPED CONCEPTION OF TASK
Troy:
Yeah … Oh, Ms. Olson, what if it’s a 8?
JOINTLY-DEVELOPED CONCEPTION OF TASK
Aaron:
[to Troy] –
Now this is what we’re gonna
162 [they both leap up onto chairs at the wall map] Troy:
[to Aaron] What’s the altitude? [meaning latitude]
Aaron:
2
“
Troy:
OK, I got 2.
“
Aaron:
Now over here. [motioning along top of map, points Troy’s finger] Now we need a red one. [jumps down to get stickers] … We just need a red one, OK? [they plot it] Let’s do the 7
“
Troy:
CO-DIRECTED STRATEGIES
JOINT OWNERSHIP OF ARTIFACTS MUTUAL SUPPORT
I hope it’s another one [on the list]! [98-12-08]
Troy and Aaron build on each other’s enthusiasm, moving comfortably in and out of explicit discussion defining task and strategies; and work on their artifacts. The space created affords joint problematizing (e.g. “There go a 8!! That’s a 8!” – “So there is an 8 here!” – “Ms. Olson, what if it’s a 8?”). Both students later reflect back on the data they have gathered and plotted in this episode later in the unit. Though their energy level and focus of attention is different from David’s and LaTanya’s, the space for reflection created in their group is very similar – mutually supportive, nonconfrontational, co-directed. It is interesting to see that this episode is from an activity (Focus Activity 1) in which David and LaTanya had not yet formed their comfort zone. This suggests that a comfort zone is a set of group norms that we might expect to find in multiple contexts, with different students, under varied circumstances. Further work on developing categories of group norms in inquiry with data, and tracking relationships between various student roles and learning outcomes within these “zones,” promises to be a fruitful direction for future research. It also promises to have direct applicability to supporting teaching practice. Other examples of the “Confrontation zone”
We can certainly see that, like the Comfort zone, the Confrontation zone created by Mario and Joel and Juan was not pre-determined by any one student’s personality. Joel’s prior group participation patterns were always confrontational, but rarely at the level of debating tasks, strategies, and interpretations, and never prompting him to propose concrete suggestions or explanations. Mario’s earlier groupings were not always argumentative – they often consisted of him giving directions, and others following or
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ignoring them. So the confrontation zone does represent a distinguishable possible set of norms, among other possibilities for these students. We can also find other examples of groups whose norms meet our criteria: •
mutual challenging rather than support;
•
hotly debated conceptions of the task;
•
competition for deciding on group strategies;
•
difficulty with division of labor; and
•
contested ownership of inquiry artifacts.
In similar groups – like Antonia and Aaron below – these norms also created temporary spaces in which reflection could happen. For example, consider the interactions between Aaron and Antonia below, as they debate their plate boundaries in Focus Activity 2: Aaron:
No, why did you do that … it’s over here!
Antonia:
No, it’s over here!
Aaron:
No it’s not, it’s over here!
Antonia:
It’s over here!
Aaron:
Alright – if that’s the edge of the plate, why are these earthquakes happening?
Antonia:
It’s another plate!
Aaron:
No it does not have to be!
Teacher:
How can you tell?
Antonia:
Lotta earthquakes!
Aaron:
I can tell because {…}
Teacher:
If it goes down here … it looks like about the same number of earthquakes …
It has to be here!
Do you need more information?
[Dalia starts drawing lines] Aaron:
No no no no – the second plate is over here!
Antonia:
So how can that just be one –
Aaron:
I think it goes like this
Antonia:
I’ll put a dot so it could be different
Clearly, the vigorous debate of interpretations of data includes connections between the emerging model of earth’s plates (lines being drawn on the transparency), data patterns (“Lotta earthquakes!”) and domain concepts (“if that’s the edge of the plate, why are
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these earthquakes happening?”). There are many examples of confrontational episodes of reflection like this one. But this argumentative mode of interaction did not always result in the adoption of more reflective roles in activity. A more common outcome is the “digging in of heels” by the more argumentative students. For example, in the Inter-American classroom, Ana is a prime candidate for the “confrontation zone.” She often disagrees with group-mates during work with data, as these sample comments from Focus Activity 1 show. These are a few of Ana’s contributions over a 20-minute period of group-work: “No, I’m highlightin’ ones that we did” “That’s wrong, cause this is north” “No, it’s gonna be over here somewhere” “What are you coloring that for?
Why you highlighting that?”
“No it shouldn’t Aaron!” “What are you doing?!?” “Hold it, no, don’t write on it!” “See y’all doing it wrong, look”
This mode of interaction leads to several arguments over the interpretation of tasks, strategies, and data, which offer opportunities for reflection. For example, she and Troy disagree about whether there is a pattern in the data the class has accumulated on the wall map: Troy:
I don’t think there is a pattern, cause//
Ana:
//I think there’s a pattern!
This discussion does not go any further until the end of the class period, but Ana has staked out her position. After a lengthy discussion in which possible patterns are debated by other students, Ana seems to want to have the last word. She is hanging on to a misconception she held before the unit began – that volcanoes happen in places where the weather is hot. (In the present discussion she conflates earthquakes and volcanoes, so the principle she is arguing is the same.) When Aaron points out data in front of her that refutes her argument, she raises her voice: Teacher:
OK – Does anybody have any questions, comments, doubts, before we wrap up for today? Ana?
Ana:
I think patterns – I think I see a pattern. [walks up to wall map] Because see, I don’t – I think volcanoes could happen anywhere, but my opinion – Aaron! – my OPINION, I think they happen in only HOT places! Cause in
165 Washington, I don’t know if it’s hot or cold. But like – [student says “Mexico”] – yeah! Mexico, and// Aaron:
//What about Alaska?
… Ana:
And my other thing to say is, I think that by each of these, it depends like if it’s – like if the volcano is, um, I think, like, if it was, like 3 to 4 [magnitude], I think that it would be more HOT, because I think the more hot, the more – volcano
The argument does force Ana to state an explicit belief, and in fact to expand her explanation (“it depends like if it’s – like if the volcano is, um, I think, like, if it was, like 3 to 4, I think that it would be more HOT”). But she “protects” her belief from Aaron’s disconfirming data by restating the word “OPINION” forcefully, as if to say “You can’t argue with what I think!” The confrontational norm of interaction never shakes her from sticking to her guns: she maintains this misconception about volcanoes right through the post-interview. In other words, argument as part of a group’s pattern of activity does not necessarily promote the adoption of more reflective roles. This may just be a matter of time – with more experience in the “confrontation zone” with complex data, Ana might find herself drawing out her “opinions” into more detailed explanations, as she does here. This could well become a reflective disposition, though here it has served the opposite purpose – preventing her from reflecting on patterns of data with respect to the data context, and instead connecting the interaction only with her conceptions of group interaction modes. But given her drawing out of her understanding in the face of confrontation, it does seem that she might be a candidate for developing more reflective roles through argument. Validity of the constructs in the research setting
In addition to validating the constructs of interactional modes and their impact on reflection and learning by examining other cases, I also sought to establish their validity for participants in the activity systems studied: the teachers and students. To establish this, I met first with each of the three teachers, and then with the students of the Boone classroom, presenting a version of the conceptual framework, the operationalization of reflection, the design intentions of the curriculum, and portions of the data analysis. The constructs of Comfort Zone and Confrontation Zone were understandable and apparently valuable to both teachers and students. In meetings with each teacher after the unit, and subsequent meetings with Ms. Mundt-Leimberer, the constructs developed in
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this study served as a basis for analyzing the learning of each student in the groups studied, and in some cases for other students as well. Constructs used in these discussions included the three contexts (data, task, and role), reflection as problematizing and connecting, and “comfort zone” and “confrontation zone.” All of these resonated with teachers as useful constructs for talking about instruction, participation, and learning. I met with the Boone students the year following the study and presented them with my analysis of how group interaction modes (specifically comfort zone and confrontation zone) mediated participation, and how participation mediated learning of concepts and reflective consideration of complex datasets. A large number of students participated in a brainstorm discussion of how group modes mediate participation and learning. Students volunteered a number of observations about how group interactions mediate individual reflection, and how this reflection mediates domain learning. The constructs seemed to enable students to develop new insights into their own practices. The teacher said afterward that the students’ discussion had given her new insights as well. These follow-up conversations suggest that the constructs used in this study have relevance and value in the context being studied. This provides an essential validity check on the work presented here, and suggests that future work can include both research and classroom applications of these constructs.
6) Discussion The goal of this analysis has been to better understand the processes of becoming more reflective, and learning through reflection in inquiry activity. I have attempted to articulate ideas emerging at the intersection of sociocultural and cognitive perspectives on learning. Learning is not change that happens only in the head, nor only in the social sphere, but rather a process occurring across this boundary. I have attempted to show how social interaction and conceptual understanding can be represented within a common framework, rather than separately as causes and effects. 6.1) What we’ve learned about reflective inquiry This study began with three questions about reflective inquiry: §
How do students learn to make sense of complex information through classroom inquiry?
§
How do students develop more reflective inquiry dispositions?
§
And how do elements of classroom activity systems interact to promote and constrain this dispositional learning?
These questions are addressed below, in a summary of several specific findings about the nature of reflective inquiry and the development of reflective dispositions. These findings are proposed in the form of five claims about learning to reflect in inquiry with complex datasets: Claim 1: The sense that is made of activity mediates the sense that is made of data Claim 2: Reflective inquiry dispositions develop out of inquiry-irrelevant dispositions Claim 3: Content learning and group interaction modes are interdependent Claim 4: Reflection in inquiry is a shared, social process Claim 5: Participation and interaction modes are sites of inquiry learning These claims arise out of the data analysis, and they both inform and are informed by the theoretical framework developed above in Section 2.
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How do students learn to make sense of complex information through classroom inquiry? Claim 1: The sense that is made of activity mediates the sense that is made of data
We have seen that students learn to make sense of complex information as part of the larger process of making sense of activity. The sense that is made of activity mediates the sense that is made of data. Classroom inquiry tasks are given meaning by participants in activity, rather than by curriculum designers or teachers alone. The relationship between students’ emergent interpretations and the meanings intended by curriculum designers and teachers is problematic – it should be determined through study rather than assumed. We have seen students make sense of data in both domain-relevant and domain-irrelevant ways, and we have seen students develop increasingly-relevant conceptions of data and tasks under certain circumstances. The process of learning to make sense of complex data has been shown to be a process of changing the ways that sense is made of activity, rather than making sense where none was made before. Every classroom interaction involves making sense, and the goal of instruction is to develop a coherent set of conceptual referents with which to reason about data – a data context. Viewing domain learning in this way, learning to make sense of complex data through classroom inquiry means developing a disposition to reflect on inquiry artifacts, connecting them with a coherent data context. How do students develop more reflective inquiry dispositions?
Reflection is a ubiquitous sense-making process, which can both contribute to and detract from the development of domain understandings. It involves problematizing elements of an experienced situation, and making conceptual connections between these problematic things and other elements of current or prior experience. Reflection can be more or less explicit, and more or less relevant for inquiry. We have seen students problematize some elements of inquiry situations (curriculum artifacts, tasks, words, etc), while treating others as non-problematic or routine. Similarly, we have seen students develop accurate domain understandings about things they have problematized, but we have also seen them make domain-irrelevant and incorrect connections to these same problematic artifacts. Our analysis suggests that reflection is central to accurately making sense of complex data in a given domain of inquiry. However, it also suggests that reflection is central to inaccurate characterizations of inquiry artifacts, and domain-irrelevant conceptions of classroom activity. Reflection is not necessarily our friend – its relationship to domain
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learning is problematic. Problematizing is not an end in itself – it is a potential step toward developing domain-relevant understandings that can guide further inquiry. We have seen examples of students problematizing patterns in data, and then using this problem to explore data-context connections. For example, during plate-mapping, David found the many clusters of dots problematic in relation to his conception of the task, and he pursued this confusion to develop theories about the number and size of plates in his region (see discussion on p. 82). On the other hand, we have seen students problematize patterns of data, and even become more adept at problematizing such patterns, without developing other connections in the data context. For example, Joel’s observations of the “big old gap” in the data during plate mapping (see p. 132) did not lead him to a conceptual connection that could be remembered later (p. 140). Even further afield, we have seen Joel and Mario problematizing observations in terms of who had the idea first; and LaTanya problematizing data items in terms of her color preferences. These are examples of students making sense of inquiry tasks and artifacts from domain-irrelevant perspectives. Importantly, our framework has enabled us to show how these apparently meaningless kinds of reflection are often closely related to the same students’ domain-relevant reflection patterns. Claim 2: Reflective inquiry dispositions develop out of inquiry-irrelevant dispositions
More reflective inquiry dispositions – those that lead to more productive reflection in the domain – do not replace less reflective dispositions. Nor are they developed from scratch, built out of newly-learned strategies. Rather, they develop out of existing modes of participation, as students redirect domain-irrelevant habits of mind increasingly toward the data context. This means that students’ patterns of domain-irrelevant reflection provide important information about how they can develop domain-relevant reflective patterns. For example, Joel’s combative mode of interaction in groups changed over time to become increasingly focused on relevant domain concepts, and increasingly productive in the group’s inquiry process (p. 141). The same disposition, earlier on, had been more personally confrontational, and had led to little or no domain learning. His increasinglysophisticated debates about data grew out of, and co-existed with, his habit of bickering. Similarly, David’s tendency to joke around during group work did not disappear as he became more reflective with reference to the domain. Rather, he continued to joke around, but his joking expanded to include domain-relevant talk (see p. 116). LaTanya’s
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tendency to connect inquiry artifacts to her personal interests was not replaced by her increasing habit of connecting them with domain concepts. Rather, she spent more time discussing these artifacts, and did so with respect both to the domain, and to her personal life (p. 110). Mario’s bossiness in small groups was not eliminated by his increasing tendency to debate patterns with his group. Rather, he added to his repertoire a habit of adopting or responding to some of his peers’ ideas (p. 142). While these observations may seem logical and obvious with respect to any one child, the larger claim has theoretical importance for research and instruction. We often distinguish between on-task and off-task behavior, or look for evidence of a student following – or not following – a particular reasoning strategy. Especially in inquiry activity, in which students are meant to take considerable responsibility for directing their own work, these kinds of characterizations should be colored by an understanding of a reasonable dispositional learning trajectory. Where might this student be heading, given her personality and the intended mode of reflective thinking? The distinction between ontask and off-task should involve not only understanding the curricular assignment, but also envisioning a reasonable trajectory from less-reflective toward more-reflective conceptions of each task. Claim 3: Content learning and group interaction modes are interdependent
Changing dynamics of group interactions are important mediators of the process of individual dispositional change. Patterns of group activity over time can afford more domain-relevant reflection in certain ways, and at the same time can inhibit domainrelevant reflection in other ways. Even when students are not working in a small group (e.g. individual work at the computer, or whole-class discussion), their reflections are mediated by their mode of participation in an activity system. For example, the development of “comfort zone” patterns of group interaction afforded LaTanya’s increasing tendency to problematize curriculum artifacts (e.g. the clay model) and some tasks (e.g. identifying boundary zones) with respect to multiple Data Context elements (real-world referents, domain concepts, and data patterns). However, the same “comfort zone” mode constrained the extent to which she problematized other tasks (e.g. debating plate predictions) and her own domain understandings (p. 101). The development of productive patterns of reflection in inquiry is a process that brings together the constructs of “individual cognition” and “social context.” The analysis has shown how intellectual and social development are intricately interconnected in observable ways. Strengths and gaps in domain learning for particular students can be
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understood in terms of the affordances and constraints of their group’s interactive mode, and their own participatory roles, for reflection. For example, David’s post-unit fuzziness about how to characterize earthquake zones other than subduction zones (see p. 117) can be traced clearly back to the lack of room for argument in the Comfort Zone (p. 101). Other students that more vigorously debated zone types understood these differences better. The conceptual understandings developed by individual students are manifestations of the patterns of problematizing and connection that developed in their group’s interactional mode, and of their own patterns of participation. The patterns of reflection that are practiced in activity are appropriated by participants. Classroom activity systems mediate what patterns are practiced, and how. This interdependence of content learning and interaction patterns suggests the unity of “learning through reflection” and “learning to reflect.” In fact, the two processes are the same: the kinds of reflection one practices establish the kinds of understandings that remain after (Hiebert, Carpenter et al. 1996). Inquiry learning is a coherent process of change taking place both in the realm of conceptual understandings, and also in the realm of modes of participation in social activity. Pedagogical discussions too often separate learning inquiry processes from domain-knowledge outcomes. Rather than concern ourselves with either learning concepts and skills or learning inquiry dispositions, we can use the framework to represent the ways changing modes of participation in activity mediate different understandings of science concepts. How do elements of classroom activity systems interact to mediate dispositional learning?
The most important question is how to characterize the learning processes of reflection in inquiry. Learning to reflect productively in a domain of inquiry is a process of accommodating one’s modes of problematizing and connecting in inquiry activity to a particular family of concepts. This has been described as bridging the Task Context to the Data Context. It is clear from the case studies that reflection in inquiry must be cumulative rather than simply repetitive: in order to build domain understanding, reflective connections must become routinized, enabling new kinds of problematizing. In LaTanya’s case, we have seen how she built from problematizing materials only in terms of group fairness issues, to also problematizing data patterns in terms of complex models and domain concepts (p. 110). Joel, on the other hand, was increasingly able to problematize relevant data patterns with his group, but built fewer and less-useful domain connections than LaTanya
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(p. 139). In both cases, we have seen how group interaction patterns enabled and constrained these students’ opportunities to build data-context connections. Claim 4: Reflection in inquiry is a shared, social process
Making sense of activity, for a given student, is part of a highly interactive process of negotiating a mode of participation in an activity system, within which artifacts and ideas take on meaning. We have seen that particular modes of participation afford and constrain particular kinds of reasoning about data, and learning to reason about data in new ways involves developing new modes of participation in activity systems. Reflective inquiry activity – problematizing artifacts (material or conceptual), and connecting them with domain ways of knowing – can be shared within and between activity systems. Holding something problematic can be a social activity, either by group construction of the problem, or through an individual sharing a problem which is appropriated by others. The case of the “big old gap” is one example (see p. 130). Joel’s disagreement with Mario about where to draw a plate boundary line eventually problematizes the line being drawn, the concept of a plate boundary, and also the curricular task of mapping the plate. This act of problematizing is shared first within their group, and then with another group. This is a very overt example of a sharing of reflection that happens constantly. Since the construction of the meaning of any given task is a negotiated process, decisions about what to problematize are shared decisions. Even the choice of words students and teacher settle on for describing inquiry artifacts significantly shapes the kinds of reflection each individual is likely to experience. When an individual student is confused or curious about something, the flow of activity can either stifle or kindle this curiosity. We have seen students begin to pursue promising lines of reflection, and then abandon them in favor of another train of thought that takes root in the group. This perspective is a shift from the way reflection is usually talked about in the literature. Reflection is commonly thought of as the quintessential individual activity. It is important for us to understand the relationship of individual thinking to various activity systems in which individuals participate. Clearly the social processes of reflection are closely related to the thinking of individual participants in activity – for instance, Joel made his observation of the “big old gap” data pattern on his own, before inserting it into group talk. Doesn’t this mean that the initial reflection was an individual activity?
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But the distinction is not this simple: Joel seems to have made his observation at least in part out of the need to take up a contradictory position to Mario. We see this in his earlier pattern in the group, as he contradicts other students’ statements often without any apparent point of reference at all. Joel often develops his data observations in order to take up his argumentative position, or even after having begun the argument without any grounds. His individual reflections are also social in nature. The social construction of reflective episodes does not negate the existence of individual reflection. We have seen in the data analysis examples of students having an individual “a-ha!” moment on several occasions. But the learning goal we set for them – to become adept at using a system of reasoning about data which is accepted in an existing community of scholarship – is at its core a social goal. It involves adopting the practices of a community (earth science inquirers), and in fact developing communal practices within the classroom. Claim 5: Participation and interaction modes are sites of inquiry learning
A social representation of the processes of reflection provides us with conceptual tools for understanding, not just how students’ thinking changes, but how we as educators can try to change students’ thinking. This is the importance of identifying connections between the Task Context, the Role Context, and the Data Context – in particular through the mediation of curriculum artifacts and teacher guidance. By locating learning within three contexts rather than one, the framework points us toward useful ways to frame instructional goals. Rather than thinking of “domain learning” and “social skills” as two different kinds of goals, we can use a sociocultural model of domain learning for framing socio-cognitive goals. The result may be a tighter connection between, for example, cooperative learning structures and curricular content standards. Participatory modes in inquiry are more than routes by which declarative and procedural learning occur. They themselves are important sites of classroom learning. Becoming more reflective in inquiry, and hence developing more robust understandings in inquiry domains, includes developing a larger repertoire of roles one can play in group interactions. This is true especially in light of the fact that different participatory modes afford domain-relevant reflection in the context of different group patterns. For example, Joel’s confrontational mode of interaction would not have afforded domainrelevant reflection in David and LaTanya’s group, but it did in Mario and Juan’s group. Joel’s domain learning opportunities will expand as he develops other modes of
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participation he can use in different contexts. Combatitiveness is potentially, but not inherently, a reflective inquiry disposition. Summary
Our analysis of small-group inquiry suggests that learning for individual students – the development of new understandings and dispositions – is mediated by patterns of activity in the “task context.” This activity in turn is mediated by the norms of the group working together, the artifacts students work with, and the teacher’s guidance – all of which contribute to the students’ conceptions of the tasks and strategies they are using. This configuration of factors interact with each student’s own understandings and role, to shape the way she thinks about her plotting stickers: as colored dots, or as earthquakes of different magnitudes. We have seen that reflection is a way students can invest the artifacts of inquiry with deeper meanings, and that individual reflection can be enhanced by being shared in the group. Our curriculum designs have attempted to take advantage of what we are learning about reflection, to provide artifacts that will afford multiple chances to reflect, from a variety of meaningful perspectives. We have tried to design artifacts that afford reflective discussions among students and teacher. We have seen that different students – and different groups – will find different elements of the situation problematic, and that this depends as much on norms and roles as it does on design. Our designs have suggested a flow of activity in which data-rich artifacts are used by students in different ways at different time – e.g. to interpret and make a predictive model, then to use this model for a subsequent modeling activity, then as a prop for telling an inquiry story. This trajectory is intended to provide multiple opportunities for different groups to problematize different aspects of these artifacts, and to suggest connections with different elements of the data context. By conceiving of reflectiveness in inquiry as a disposition which develops through individual roles, in a space defined in great part by interactional modes, we lay the foundation for rethinking both instruction and curriculum design. The framework locates both instruction and design in a relationship with the data context and the role context. In the next section we revisit some of our design assumptions in light of this perspective.
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6.2) Design implications While evaluation of the Earth Structures and Processes curriculum is not the intent of this study, it is worthwhile to point out some implications of the analysis for design considerations. This section provides a brief overview of design issues for curriculum materials, and then design implications for group work. Design implications for curriculum: revisiting two design approaches
The case studies highlight some design issues for each of the two broad design approaches used in this unit (discussed in Section 4.4): iterative re-design of models from data, and using a trail of artifacts to teach other students. In this section we revisit these assumptions underlying the design of curriculum artifacts, in light of the patterns of activity and reflection observed in the enactments. These patterns suggest some design issues to be addressed in refining the two approaches. Design Approach 1 revisited: Iterative re-design of models from data
Our first design approach was to provide materials from which students could make a series of models from complex datasets. Each model created by students was meant to be used as a resource in the next phase of data interpretation, building in iteration and reconsideration of interpretations without just saying “Do it again.” This design approach met with mixed results. Some artifacts were more frequently reflected upon by students than others. And some artifacts seemed to have more of the students’ data interpretations “inscribed” into them than others. The concepts of plate boundaries and boundary zone types were the ones best inscribed in students’ inquiry artifacts, and they seemed to be among the best-learned concepts as well. The connection of data patterns and domain concepts back to actual earthquakes in real places was uneven. The kinds of reflective connections made by students during the earthquake-plotting activity (e.g. Joel, Marie and Mario’s discussions about the Midwest earthquakes, discussed on p. 78) were not returned to as objects of reflection during the next round of investigation. This could be in part because no re-designed artifacts remained at the small-group level representing the plotting activities – only the wholeclass wall map. Valuable reflections happened in each of the classes in great whole-class discussions after the plotting activity, but the bridge connecting this activity to the rest did not remain in the form of a group artifact.
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The various models made in the groups served as valuable connections for explaining work missed by one group member or the other when they were absent. We have seen the part that the models played in affording joint attention to interpretations, and debate. The artifacts also helped the teacher mediate problems in the groups. In moving from Focus activity 2 to Focus activity 3, it was the flexibility of the Progress Portfolio’s artifacts that helped the teacher keep the Comfort Zone together. David and LaTanya were able to create separate pages for their different interpretations. This feature of the artifacts got them out of a rut, and enabled them to accommodate differences of interpretation within their agreeable process. Without designed models to make the argument concrete, the teacher would have nothing to look at to understand the disagreement, or to model a solution. The process of capturing interpretations in the series of models gave the Confrontation zone group great opportunities to debate the data. Joel could point to specific problems with Mario’s line; Mario could bring up specific captured screen images to refute Joel’s proposals. The artifacts sometimes gave a false sense of closure to groups’ processes. Once the separate prediction pages were established, their differences were never debated again. Once the plate boundaries were agreed upon, most students did not go back to question them. Thus the ability to put a confusing situation “in a box” – by making it into an artifact – cut both ways. The interim artifacts played an important part in David and LaTanya’s development of their comfort zone. For LaTanya, they gave her a connection between her identity and the inquiry – as when she named her plate after her cousin, and referred repeatedly to “my clay plate.” LaTanya’s identification with these artifacts kept David connected with the group process at times when he might otherwise have moved away from it. Ownership of particular artifacts seemed to be a good bridge connecting many students to the inquiry. Conflicts over ownership sometimes alienated individuals from the inquiry, as when Joel had no connection with the contents of the presentation pages. Design Approach 2 revisited: Using a “trail” of designed artifacts to teach other students
The second design approach to promoting reflection was to provide students with a trail of their own designed artifacts from which to construct a narrative. In both classrooms that used this lesson, there were many examples of students taking advantage of it as an
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opportunity to reflect. Some students returned to the computers again and again during this phase, trying to get a clearer handle on “what’s going on on my plate.” The intended coherent progression of unit activities was not always well represented in the trail of artifacts created by students. In particular, the products of the staging activities did not always “suggest” a connection with the inquiry activities. Those that were mentioned often in whole-class discussions (e.g. some of the “information sheet” details) were remembered by students as they made their presentations. But the mythology and modeling activities clearly did not fit in as part of the story of the inquiry. We have seen that this phase did not prompt David and LaTanya to reflect on the complexities of data analysis in preparing their presentation, even when prompted. Instead, they stayed in the more comfortable territory of taking David’s notes (domain concept definitions), and turning them into models for demonstration. This was certainly a reflective process, and it certainly built on the modeling activities of the unit (plate models, hand motions, earth structure models). But it left the aspects of their investigation that were potentially very fruitful – figuring out which way the plate was moving, even problematizing certain plate boundaries – hanging at the end. Mario, Joel and Juan had a different problem building their presentation. Mario dominated the computer time for constructing their Progress Portfolio presentation, and the three had trouble agreeing on their narrative. Joel’s problematizing of earthquake patterns was not inscribed in their finished artifacts. In short, their designed artifacts did not do justice to the complex discussions of data that went before. The curriculum artifacts seemed to serve the development of the “confrontation zone” very well, providing enough complexity to promote debate. But in the process of reworking and creating models from these artifacts needed to embody more of the disagreements, in order for this group to reflect back on their understandings during the final phase. The trail of artifacts played a valuable part in enabling all students to be “teachers” in the final activity. While more academically-inclined students did more talking in this phase, all students were able to contribute to the presentations. If these had been based solely on notes and understandings, this “teacher” role would have been played only by topachieving students. In this sense the trail of artifacts enabled a valuable role in activity for all students.
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Design questions
There are certain design questions that arise from these considerations of the role of artifacts in promoting reflection: 5.
How can artifacts mediate connections among all elements of the data context?
6.
How can artifacts inscribe differences of interpretation, while still affording debate?
7.
How can artifacts connect whole-class processes with small-group processes?
8.
How can artifacts afford both small-groups’ and individual students’ sense of identification?
9.
How can artifacts inscribe the confusions that happened – not just the clear understandings – so that they are explainable?
These questions are posed here as valuable issues to explore in future design research. Some of these questions are engaged in our re-design of the unit, described below. Re-design of the unit
At the end of the school year I met with three teachers, and a fourth teacher separately, to discuss ways to improve the design of the unit. All agreed that the main problem to be solved was one of flow – better clarifying the relation of one phase to the next, and building in better efficiency of transitions between phases. One way that we decided to accomplish this was to connect all phases of the inquiry through geographical place. It was disorienting to have students study one earth structure in a staging activity, build a model of a different structure in another, plot earthquakes for a different region of the world, and then be assigned a plate in yet another. We decided to assign each group an earth structure that they would follow through all activities from the beginning to the end – building essentially a very deep case study. We decided that the materials for creating the various models should also suggest the connections among the different activities. All maps used for the different activities (staging activities, plotting earthquakes, plate mapping, identifying zones) should be made on the same scale, based on similar map representations. This would help suggest connections among phases. By connecting the different activities, we hope that this common focus on place and common representation will prompt reflective connections among elements of the data
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context. If individual earthquakes are plotted around the Java Trench, and later plate line predictions are drawn for the plate around the Java Trench, on maps that are at the same scale – we hope that this will prompt reflection connecting the events with the data pattern with the domain concept. We also hope that this change will afford reflection back onto earlier confusions, not just settled understandings. For example, unclear patterns at the end of Focus Activity 1 may be connected – through common place and common representation – with the more settled lines decided on after Focus Activity 2. In revisiting these related models to construct the final presentation, the earlier confusions will be inscribed in the earlier models, in a way that they were not with the less-connected activities of the last version of the curriculum. The issue of how artifacts can help connect the different modes of classroom work – whole-class, small-group, and individual – is less clear. The approach followed in our unit re-design requires cross-pollination among groups, since each group focuses on one place throughout. This is built into the unit design through various “jigsaw” lesson structures, and the mini-conferences for plate mapping. The extent to which these structures unify students’ understandings across groups remains to be seen. Implications for designing group work
The data analysis presented in this study suggests the importance of another kind of design work which teachers do: the design of student groups for inquiry. Without attempting an in-depth study of how the present findings can inform group-work design, this section suggests some implications worth considering. We have seen the ways the combinations of different students’ roles created different interactive spaces, and the ways these spaces in turn mediated both content learning and role development for each student. It is clear that the coming together of different types of discourse can make and break learning opportunities in a group. Gutierrez et al (1999) have explored the ways such “hybridity” of discourse styles in a group has the potential to foster creativity, generativity, and discovery in discussions. We have seen this, for example, in Joel and Mario’s convergence on data-focused debate as a mode of interaction, in contrast to either boy’s mode in his previous groupings. Similarly, the outgoing LaTanya and the quiet David were able to bring their voices together in a productive mode that incorporated strengths of each in analyzing data. The
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challenge for teachers is to establish interactional norms that allow these different voices to be heard, rather than shut down or drowned out. Students in a group co-construct the meaning of the task they are working on. A productive group-interactional mode is one in which this process incorporates reflection, connecting classroom activity with the data context which gives it domain-relevance. We as educators must learn to identify patterns of group interaction – norms of “table talk” – that promote and hinder this process. This study suggests that these patterns will not be generic – rather, the value of a particular group mode varies with the roles adopted by each group member. We have seen some affordances and constraints of two groupinteractional modes for this kind of reflection: a “comfort zone” and a “confrontation zone.” We have seen how particular student roles interacted with these group modes to mediate learning in a variety of ways. It seems that both kinds of zones are helpful for different kinds of reflection, but neither is always helpful. Promoting confrontation in all groups would not necessarily be a good thing – it could drown productive debate in mindless disagreement, as in Mario, Joel and Juan’s dissolution during the final “presentation preparation” phase of the project (see p. 135). Promoting a comfort zone in all groups would not always be a good thing – it might promote the kind of let-it-be attitude that kept LaTanya and David from pushing deeper (see p. 101). The important work lies in understanding how the roles adopted by individual students indicate what kinds of group interactions are likely to develop their reflectiveness. Sometimes an existing role (or individual mode of participation) for a student might valuable to explore more fully; sometimes it might be better to try a new role. A good goal across the school year might be to ensure that all students start by developing those dispositions that they begin the year with – their “native resources for reflective thinking” – by pairing them with others who will bring these strengths out. But afterwards, students might be challenged to push themselves into other directions, seeking to develop roles to bring out other valuable resources that are less familiar to them. The constructs of “comfort” and “confrontation” as group resources for reflection are worth pursuing in more depth. Particular lesson structures seem to lend themselves to fostering the development of each of these in different ways. For example, we have seen that structured debate over data interpretations – like Focus Activity 2’s “miniconferences” for plate mapping – afforded valuable domain reflection in the Confrontation Zone, but not so much in the Comfort Zone. David and LaTanya were not
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able to engage in this activity very productively, as suggestions of differences of interpretation were met with frustration (LaTanya with Juan), or sarcasm (David with Ben). In contrast, Joel’s arguments with Mario often led to a valuable kind of problematizing during plate mapping, that sometimes ended up being shared throughout the table group and beyond. This kind of confrontational group reflection can be cultivated in the classroom, making its value explicit for groups that are less comfortable with that mode. In whole-class discussion, more argumentative groups might be highlighted to point out the process they went through, and the teacher can underline the productive side of confrontation. The same holds for the reflective potential of more harmonious interactions. The comfort zone led to a far more productive period of reflection on the finished investigation, during presentation preparation (focus activity 4) than the Confrontation zone. David and LaTanya spent extended periods of time thinking about how to explain the concepts, whereas Mario, Joel and Juan disintegrated into argument over who gets credit for what, who gets to say what, Mario’s need for control, and Joel’s pushiness. They had trouble maintaining a collaborative mode of work needed to culminate the project reflectively. However, the Comfort Zone also led David and LaTanya to focus more on nonproblematic models and concepts than on the stickier data interpretation issues. During such activities, when the value of a comfortable mode is evident in a given group, the comfort zone might be spotlighted, asking students to share how they co-constructed the story of their investigation, and came to agreement on the nature of their findings. Groups like Juan, Joel and Mario’s could benefit from this kind of explicit discussion of comfort zone norms. Similarly, their feedback to the comfort zone group might prompt more rigorous questioning of their understandings. Thinking about reflection in terms of both individual and group interactional modes can give us insights into designing instruction. Rather than envisioning a universal trajectory of development for all students – from less-reflective to more-reflective – we can think of groups as spaces for developing students’ different resources for reflection. This development is certain to happen along a number of different trajectories. We might benefit from studying some common roles adopted, for example, by high-achievers, lowachievers, and others in groups. Common roles of all of these students can be analyzed to identify affordances and constraints for reflection of each, and also for ways that they interact with one another and with group norms.
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As teachers we often have deep tacit knowledge about how groupings might be good or bad for an individual student. I propose examining this tacit knowledge from the perspective of group-design principles, in particular for group inquiry with complex data. The present study suggests some straightforward observations to begin building this explicit understanding. For example, a “comfort zone” can provide a relaxed space in which otherwise-peripheral students can spend good amounts of time interacting with data and sharing observations – increasing opportunities for reflection. However, within the “comfort zone,” differences of opinion that could be valuable sources of reflection may be glossed over, to maintain the easy interactions. The conceptual framework developed here adds value in its potential for characterizing these affordances and constraints for reflection in group norms and student roles, and also in its scheme for relating these social interaction patterns with the intended domain of inquiry.
7) Conclusions and future research
The framework developed in this study is meant to suggest an approach to studying learning. The heart of the approach is finding relevant representational schemes to connect cultural, conceptual, and activity-bound perspectives on change in an activity system. Future work in this vein may enable us to characterize factors mediating learning with a good deal of contextual validity – building our understanding of how culture, activity, and knowledge connect with one another in everyday activity. Jean Lave’s admonition not to impose categories like “expert/novice” on situations which are better understood using the constructs “jock/burnout” (Lave 1990) should not lead us to study the social and ignore the academic-conceptual. Rather, Lave’s point is that we need to understand the social and academic contexts of activity in their relation to one another. I propose that we attend to conceptual understandings as part of the role/identity context, while at the same time attending to their relationship to instructional designers’ intentions in the data/domain context. Patterns of social interaction are the arena in which these two contexts interact. These mutually-informing perspectives should not be separated. The specific graphics and constructs developed here are not meant to be generically applicable to all other classroom inquiry studies. Future work to develop this kind of approach should propose other representations of culture, identity, and activity systems, which enable us to identify foci of reflection. Our goal should be to find multiple systems for representing participants, curricular constructs, and classroom activity, maintaining the integrity of each of these constructs, while attending to the most relevant connections among them. Future directions: Foregrounding other perspectives
Reflection, as operationalized here, promises to be a productive lens through which to analyze activity. Reflection in small-group inquiry activity, without the teacher’s immediate presence, seems to take on a different character than reflection in whole-class discussion, or reflection during individual work. These differences can be productively explored in an attempt to further develop the constructs of reflection, problematizing, and suggestion proposed in this study.
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This study has not investigated the complexities of teachers’ roles in classroom inquiry activity systems. Representing these roles as more than one element of the task context (“teacher guidance”) will be a big step forward in developing this kind of framework. While a teacher is one participant in activity, and as such can be represented using the role context (as with students above), the unique mediational role of the teacher might be better represented as a fourth context, the instructional context. This approach would enable us to focus on the relationship between the teacher and each of the other three contexts, a valuable perspective for understanding teaching strategies and teacher learning. Dispositional learning has been explored here within a particular activity context – the development of interactional modes (roles) which afford reflective connections between an activity system (task context) and a family of conceptual understandings (data context). The question of “transfer” – the viability of newly-developed reflective dispositions in other settings – may be reconceived in this framework as role development across activity systems. Understanding transfer in this way requires us to examine more closely the relationships among roles, understandings, and identities. We can pursue this line of investigation by foregrounding what I have called the role context, and examining its relationship to multiple activity systems (task contexts) with respect to particular domain understandings (data context). This could include looking at non-inquiry activity, less-structured inquiry, whole-class discussion, and any number of other common patterns of classroom interaction. Similarly, the value of particular curriculum artifacts for mediating access to domain understandings could be a foreground focus of such a study. For this purpose we would expand the “artifacts” element of the task context, examining its relationship to the Data Context. This perspective could tie learning outcomes more directly to design intentions, grounding this work in curriculum design principles. Connecting the framework with concrete learning objectives
In the analysis presented above, individual students’ conceptual understandings in the domain (before, during, and after the unit) were identified using traditional pre-post interview data and other evidence. However, precise states of understanding of particular concepts (e.g. how accurate is a student’s characterization of the direction of plate motion at a buckling zone) are not represented in the three-context framework. Rather, the framework is used to represent changes in patterns of reflection.
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But specific conceptual learning objectives (e.g. student should be able to define and identify a buckling zone) should not be seen as separate from the framework proposed here. A set of specific understandings central to the domain underlies the representation of the Data Context. If we were to annotate the elements and connections of the Data Context, we could represent such understandings in great detail, even in such a way that they could become test questions (see Figure 2.3 on p. 22 for an example). This would be the next level of detail at which the proposed framework can be used to study learning. The framework can also be valuable in developing learning goals of a different kind – dispositional learning goals. By grounding dispositional development in terms of domain-relevant reflection, it moves this kind of development out of the category of “social skills” and brings it more centrally into focus as a primary target of instruction. Role in activity becomes a formally recognized site of learning in the framework developed here, providing us with language to frame learning goals for developing reflective inquiry dispositions. Future work in this vein can seek to understand particular trajectories of dispositional learning that could be valuable for a wide range of students, and the relationships among various types of group interactional modes, teaching strategies, curricular designs, and individual students’ dispositional learning. Conclusion: learning as a coherent change process in multiple contexts
The heart of this approach is conceiving of learning as change of individuals with respect to activity systems, identity, and conceptual relationships. I have attempted to represent the unity of these three contexts in one coherent view of change. The value of this view will be measured in our ability to use it to design effective instructional tools.
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Appendix A: Interview protocols There are two interview protocols: one for individual interviews conducted with each student before and after the unit, and the other conducted with a group of three students together, before and after the unit. The former included one additional set of questions for the post interview, using a new map representation and requesting a comparison of any two mountain ranges. The latter utilized different data maps and a different task charge for the post activity, as indicated in the protocol.
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Protocol 1: Individual interview -- 15 min. MATERIALS: §
Rand McNally world map
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Maps of Americas and EurAfrica, with and without data (attached below)
[Do 2 students starting with Americas map, and 3rd starting with EurAfrica -- each day.] Introduction
This interview is for us to find out your thoughts and ideas about the earth and some maps. This is just for our study at Northwestern, and nobody else will see it. Don’t worry about answers being right or wrong -- just say what you really think. This doesn’t affect your grade in class, it’s just for our information. World map
[Using R-M world map] Here’s a map of the world. Can you show me anything that you recognize on this map? [If prompt needed] Any oceans, places, that you think you know what they’re called? What’s a continent? Can you point to one on this map? [If yes] Can you name any of the continents? Oceans and depth
Can you name any bodies of water? What does this map show you about the oceans? Where do you think the ocean is very deep? Where do you think it’s very shallow? Why do you think so? What might cause it to be deep or shallow? Altitude and mountains
Have you ever heard the word ALTITUDE? What do you think it means? [If don’t know:] Altitude means how high a place is above sea level.
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What might be a place in the world that has a high altitude? Can you show a place on the map that might have a high altitude? Why do you think that’s a high altitude place? [If they haven’t pointed out or mentioned mountains] Let me ask you something about mountains. Where are some places in the world where there are mountains? Can you point to them on this map? [If they can’t, point out three mountain ranges] Here are some mountain ranges: over here are the Andes Mountains. Over here are the Himalayas. Over here are the Rocky Mountains. How do you think these mountains come to be? How do they form? Why do you think there are mountains in these places, and not in other places? [If they have an explanation or a guess] Why do you think so? Is there any information you could check to see if your idea is right? Earthquakes
I’d like to ask you about earthquakes. Have you learned about earthquakes before? Where? What did you learn? Can you explain what an earthquake is? What exactly happens when there is an earthquake? What kinds of places do earthquakes happen? Can you name any specific places where they happen? Are there some places where earthquakes DON’T happen? Why do you think they happen in those places, and not in other places? How often do you think earthquakes happen? When do you think the last earthquake was, anywhere in the world? What do you think causes earthquakes to happen? [If they have an explanation or a guess] Why do you think so? Is there any information you could check to see if your idea is right? Volcanoes
I’d like to ask you about volcanoes. Have you learned about volcanoes before? Where? What did you learn? What is a volcano?
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Where do you think volcanoes happen? What kinds of places in the world? [If no, then ask:] Could they happen anywhere, or only in certain places? Why do you think they happen there? Can you name any specific places where you think volcanoes might happen? Why do you think they happen there? [If they have an explanation or a guess] Why do you think so? Is there any information you could check to see if your idea is right? Plate tectonics
Have you ever heard of plate tectonics? Where did you hear about it? What does it mean? What is a plate? Could you point to one on a map? Interpreting a map showng volcano data
[Show hemisphere blank map] What do you recognize on this map? [If needed:] This is a map of one side of the world -- this is North America, and this is South America. This is the Atlantic Ocean, and the Pacific Ocean. Where would you predict volcanoes might erupt, on this map? Why do you think they would erupt there? [Show hemisphere+volcanoes map] This map shows places where volcanoes have erupted. What do you notice when you look at it? Where are there volcanoes? [If they don’t mention any patterns] Do you see any patterns of where volcanoes are? [If they say they see a bunch together, or a line, blob, pattern, etc] Could you show me where that is? Where does it start? Where does it end? Is there anything that surprises you about the volcano locations on this map? [If so] Why is that surprising to you?
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Why do you think that [pattern, blob, line, bunch -- whatever word they use to describe it] of volcanoes is right there? Why might they be there? What could it mean? [If they don’t know] Just take a guess -- why might there be volcanoes there, and not so much in other places? [If they give any guesses or hypotheses] Where else might you expect to see more volcanoes in the future? Why there? [Show other hemisphere blank map] Now this is a map of another part of the world. Do you recognize any places on this map? Now after seeing that last map, where would you predict volcanoes probably would be in this part of the world? [If they can’t predict] Think about the kinds of places that had volcanoes on the last map [show map] -- what kinds of places had volcanoes there? Can you find similar places on this map? Closing
Thanks very much for your help! Do you have any questions for me?
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Protocol 2: Group inquiry task
Part 1 – 20 minutes Materials: •
(1) Map of L.A. area with names of different cities/suburbs
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(2) Map of median household income for the L.A. area
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(3) Map of people under 18 for the L.A. area
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Erasable (water base) color markers
Students: A group of 3 students Instructions to students: We are going to ask you some questions related to things you may have done in your science class or will be doing this year. This activity is similar to one you did before your class started the plate tectonics unit. It will take about 40 minutes. This is for our research, so it doesn’t affect your class grades in any way. We are videotaping this session, but the only people who will see it are researchers at Northwestern University. There are no right or wrong answers to these questions. We just want to know what you think, so don’t be afraid to talk about any ideas you have. A. Recognition of L.A. street map Give students map (1). Do you recognize anything on the map? (2 - 3 minutes) B. Finding “What’s interesting” about a map For this part of Part 1, use map (2) first with one student group; switch the order and use map (3) first with a second student group, if there is more than one student group being assessed. Give the students map (2) or (3) to look at. Leave map (1) where they can refer to it if they want. Here’s a different map of Los Angeles. What do you find interesting on this map? (5 minutes) Some general prompts if students are not responding: •
What’s something interesting that this map tells you?
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Why is that interesting?
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What on the map tells you that?
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How do you know that?
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What else on the map do you think is interesting or surprising?
Some Level 3 prompts that could be used after it is apparent that no level 3 statements are made without assistance: •
One way to make interesting observations is to compare -- Is there information on the map that is interesting when you compare different locations?
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Do you wonder about why certain incomes (or age groups) are in certain locations?
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Are there any other interesting patterns that you see from the map? How do you know?
Some Level 4 or 5 prompts that could be used if students make any kinds of generalizations: •
Is that always true? [In response to some pattern or generalization]
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Is there anything you know about or have learned before that would make you think that is true or not true?
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Do you have enough information to know if that’s true?
C. Predicting and Finding “What’s interesting” about a map For this part of Part 1, use map (3) or (2) – whichever one wasn’t used in B above. Give students the L.A. map (1) again and a red and a blue marker. Ask them to make a prediction: (given them about 2-3 minutes) On this map, where would you predict that you would find the largest populations of people under the age of 18, compared to other areas on the map? Mark your predictions with this red marker. If the household income map is being used, change the question to: On this map, where would you predict that you would find the largest populations of people with the highest income, compared to other areas on the map? Mark your predictions with this red marker.
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After 2-3 minutes, ask them to make a second prediction (give them 2-3 minutes for this as well): On this map, where would you predict that you would find the fewest people under the age of 18, compared to other areas on the map? Mark your predictions with this blue marker. If the household income map is being used, change the question to “lowest income.” Give students map (3) or (2), whichever was not used in “B” above. Here’s a different map of Los Angeles. What do you find interesting on this map? Give students about 5 minutes for this task. As needed, use the same prompts as in B, above, to elicit responses about the map.
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Part 2 – 20 minutes Materials: •
(1) Map of L.A. area with names of different cities/suburbs
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(2) Map of household income for the L.A. vicinity
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(3) Map of people under 18 for the L.A. vicinity
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(4) Map of number of movie theaters in L.A.
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(5) Map of total population in L.A.
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(6) Map of percentage of population in L.A. that is Black
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(7) Map of percentage of population in L.A. that is Hispanic
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(8) Map of percentage of population in L.A. that is Asian
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(9) Map of percentage of population in L.A. that is White
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Erasable (water base) color markers
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Post-it notes
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Blank paper
Write on the board: “Things we want to know more about”
A. Task to recommend a neighborhood for a new movie theater complex In 1992, Magic Johnson, former all-star NBA basketball player, wanted to do something that would make a difference in Los Angeles. He built a successful movie theater complex in an area known as Baldwin Hills. This area had been previously ignored by the big theater chains. He proved that movie theaters could be successful in lover-income, non-white areas of the city. Over 50% of his business came from people ages 12-24. Now Magic wants to build a similar movie theater complex in another part of the Los Angeles area. He wants it to be an area that is similar to Baldwin Hills in income and other types of demographic data. There’s one exception. He wants the new theater complex to be available to minority ethnic groups that are different from those found in Baldwin Hills.
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Now I want you to imagine that you are part of a team that is helping Magic to write his business plan and decide on a location for the new movie theater complex. You must come up with a recommendation for the location. In addition to the two maps that you already looked at, there are some other maps that might be helpful. When you pick a location for the theater complex, you will have to explain why you picked it using information on these maps. You’ll have 10 minutes to do this, and here are some special instructions: 1. You can use any of these maps. 2. While you are talking, but before you make a final decision, use the markers to circle any locations you are considering. 3. By the end of the 10 minutes, the group has to agree on one location that they want to select. On this map (pick one map to do this) you should mark the location you decided on with a marker. I’ll let you know when you have must a couple of minutes remaining. 4. If there’s other information you want or questions you have, but can’t find the answers on these maps, tell me and I’ll make a list of those things on the board. 5. You can use any of these markers, post its, or blank paper if you want them while you are considering locations. Ask: Now someone summarize for me what you are going to do. Remind students after 5 minutes and after 8 minutes how much time they have left. Even if they haven’t come to a final decision at the end of 10 minutes, they will need to stop.
B. Debriefing the group’s final choice– 5-10 minutes Ask students questions about the location they considered (the ones they had circled before making a final decision): What locations did you consider? Why? What data from the maps led you to consider that location?
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Why is that an important criterion to use for picking a location for the new movie theater complex? Ask students similar questions about the location they ended up selecting. What locations did you finally select? Why? What data from the maps led you to consider that location? Why were those important criteria to use for picking a location for a new movie theater complex? You used these criteria (these maps) for picking the location. Is there any reason why you didn’t use the other maps? Would Magic and other members of the business plan team be satisfied that you have been thorough about finding a location? Do you think you used enough data? What else would you want to know to make a sound decision? Why? C. Comparing this activity to previous activity How would you compare doing this activity this time with when you did it before the plate tectonics unit and had to find a sister school using Chicago maps? Was it any easier or harder this time? Why? D. Conclusion We have to stop now because we are out of time. Thank you for participating. You did a nice job. Please don’t tell your other classmates about the maps that you looked at, because they may need to do the same thing with us later.
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