Session M1H
Bridging the Gap: Cognitive Scaffolding to Improve Computer Programming for Middle School Teachers Terence C. Ahern West Virginia University,
[email protected] Abstract - Serendipity is a program targeted at middle school teachers with the goal of implementing dynamic system modeling across disciplines. The project targeted 3 teachers: science, math and social studies. Serendipity began during the summer where they were introduced to StarLogo, simulation software built on Logo. The goal was for each teacher to develop and to integrate a model into their core discipline. At the end of the summer the teachers had developed targeted models: FoodWeb, BandWagon and Debit or Credit. In order for the teachers to be able to program StarLogo effectively they had to conceptualize how they could use the software to teach important concepts in the core discipline. Index Terms – cognitive scaffolding, Instructional Design, scientific inquiry, StarLogo INTRODUCTION
choices. Scientific knowledge is a critical skill for the 21st Century. This downward trend implicates the type of curriculum being taught at the middle school level. Zimmerman, Raghavan and Sartoris point out that “at the middle school level, instruction emphasizes content more than process, and the content is often abstract and complicated” [2, p. 1248]. “Schools are designed to present established understandings, not to promote discovery of new knowledge” [3, p. 1880]. Essentially, middle school students learn how to use formulas or algorithms in the abstract; unfortunately they do not learn how to how to apply these formulas and algorithms in the context of real-world problems. “The ensuing culture of conformity with established knowledge is the very antithesis of scientific inquiry”[3, p. 1880].
The problem with this type of learning, which Ausubel [see 4] calls rote learning, is that it is fleeting, students cannot recall the information they learned. In contrast, more meaningful learning has 4 important advantages: knowledge is retained longer, the capacity for further discipline-based learning increases, the opportunity for learning in related disciplines expands, and finally the ability to apply the new knowledge with new problems or in new contexts improves. Changing the curriculum is difficult. As Hanauer points out “Scientific research typically involves complex methods and problem-solving approaches, resulting in conclusions that are subjected to worldwide evaluation. Capturing these characteristics of professional science within the K-12 school classroom is daunting” [3, p. 1880]. One way is to improve the way students in classrooms talk about science.
The National Center of Educational Statistics (NCES) tracks the performance of students through The National Assessment of Educational Progress (NAEP), which is referred to as "the Nation's Report Card”. In 2005 NCES conducted an assessment of grades 4, 8, and 12 to find out how well students did at conceptual reasoning, scientific investigation, and practical reasoning (NAEP). In grades 4 and 8 the students are generally performing well but the overall trend is troubling. The report indicates improvement in the average score in the fourth grade with low, middle and high performing students all showing gains. However, in the eighth grade a troubling trend emerges. The data indicate no improvement in the eighth grade scores and by the time EPISTEMIC DISCOURSE these students reach the 12th grade the scores show a downward turn. As reported in the NAEP “In 2005, the Chin states that “When students learn science in a classroom average science score for twelfth-graders was 3 points lower setting, a primary source of information input comes from than in 1996, but statistically unchanged from 2000” [1, p. teacher talk and teacher–student interaction” [5, p. 1342]. However in most classrooms the form of classroom 31]. This breakdown in middle school science is troubling discourse is based on the recitation model, i.e., the teacher because the modern world demands sophisticated science poses a question, selected students respond and the teacher literacy. Only a short while ago swamps were considered then evaluates the response (IRE). [5, p. 1342]. This form of unhealthy and were marked for destruction (i.e. drained). A classroom discourse does not reward further interaction. hundred years later we know that swamps, now referred to Because the teacher already knows the answer the question as wetlands, are an essential part of an ecosystem. The is merely confirming or evaluating and closes off any further However, as Ahern observes through true media is full of stories on subjects ranging from greenhouse dialogue. gases to more fuel-efficient cars that require a high level of “collaborative discourse, student and teacher or student and sophisticated scientific thinking in order to make informed student, engage in an interaction that leads them to make 978-1-4244-4714-5/09/$25.00 ©2009 IEEE October 18 - 21, 2009, San Antonio, TX 39th ASEE/IEEE Frontiers in Education Conference M1H-1
Session M1H meaning of the content and to incorporate it into their cognitive repertoire. These activities are discursive in nature, writing, verbal interaction, and presentation that ‘focus on knowledge and understanding, rather than on procedures’. In other words ‘the medium for skill practice is action while the medium for reflection is discourse’. The process of this understanding is cyclical and iterative.” [6, p. 297]. Consequently, moving to a more scientific form of classroom discourse requires opportunities for more openended “what if” questions that require testing and finally interpretation. Moving from a recitation model to a more scientific form of discourse – observe, question, test, interpret - is difficult for teachers. As Chin observers “Lines of discourse need to be developed where students are continually engaged in various cognitive processes such as comparing, hypothesizing, predicting, explaining, interpreting, inferring, and reflecting” [5, p. 1342]. One effective way for teachers to create more opportunities for scientific discourse is to use artifacts, which provides a focus for the interaction. Roth notes that “artifacts acted as conscription devices in the sense that they (a) permitted students to engage one another by making direct reference to the artifact (pointing, gesturing), (b) focused participant's attention and communication, and (c) serve to represent the knowledge negotiated and constructed in the pursuit of some goal” [7, p. 148]. Computer-based dynamic models create accessible artifacts for any teacher to use.
science or math disciplines. The key to integrating modeling and simulation software in the classroom is for teachers to become comfortable using it. However, the biggest hurdle for teachers is not the learning of particular software but the developing of dynamic system models [see 11]. SERENDIPITY
Serendipity is a project that integrates dynamic systems modeling into the classroom in order to do data analysis and computation [see 11]. The goal was to have teachers develop and integrate models as artifacts that will stimulate epistemic discourse in the classroom.
DYNAMIC MODELS
Models make abstract entities visible and concrete, and they can simplify complex phenomena, omitting all but the essential features or components. “Models can depict relationships, organizing key elements of a system into a coherent structure. Each component can thus be viewed not as an isolated fragment, but as part of an integrated system, with clearly defined connections to other elements within that system” . In the National Science Education Standards, models are included among the unifying concepts and processes that offer “insightful ways of thinking about and integrating a range of basic ideas that explain the natural and designed world” [8, p. 115]. Wiseman, Adams and Perkins report that a “well designed simulation focuses the students’ attention on the basic scientific concepts. When something unexpected happens, the student questions her understanding and changes parameters in the simulation to explore and improve her understanding – approaches similar to those taken by a scientist working with an experiment [9, p. 682]. Penner, Lehrer, and Schauble agree and suggest a higher level of epistemic reflection takes place because once the model is “instantiated it is necessary to consider the degree of match between the phenomenon being studied and one’s model: Does the model capture the phenomenon” [10, p. 430]? The model is not an end in itself but generates more inquiry. This is where dynamic systems modeling can be used effectively throughout the curriculum and not simply in
FIGURE 1: SETTING UP THE INITIAL STATES
Serendipity uses StarLogo [12] for its modeling software. StarLogo was chosen because it reduces the syntactical overhead of traditional programming languages by its unique drag and drop programming metaphor [11]. This made it very easy to model dynamic systems using rule based agents. Building a dynamic model requires four basic elements: defining the initial state, developing rule-based agents, implementing a process for interaction and a response to feedback. Creating models in StarLogo is straightforward programming. For example StarLogo defines a command block called setup, which initializes the model. As seen in Figure 1 the model is built around a variety of individual agents. For this model, for example, there are 30 different Buster (Rabbits) created and randomly scattered throughout the design space.
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Session M1H Additionally, because StarLogo uses an object oriented design approach creating multiple agents with unique sets of behaviors is simple. As illustrated in Figure 2 each of the agents can have predetermined characterizations such as Homer Simpson. The software also makes it easy to brand agents by uploading a simple JPEG graphic. Once the model is running each of these agents behave and react individually.
As indicated in Figure 4 this makes it very easy to program different feedback routines based on the required algorithms needed by the model. Even though the programming was easy it is not trivial. Given the relative ease of learning how to program in StarLogo we wanted to know what the “barriers” were for integrating dynamic models into the middle school curriculum. STUDY Participants
FIGURE 2: INDIVIDUAL MULTIPLE AGENTS
StarLogo makes interaction extremely easy due to its Logobased heritage. With simple drag and drop programming the various agents can move around in the environment as illustrated in Figure 3.
The case study was conducted with 3 middle school teachers who were all designated as highly qualified as defined by the No Child Left Behind Act (NCLB). The teachers had an undergraduate degree and were certified in their content area. Finally they all had been teaching for more than 3 years [13]. They were all very adept with and comfortable with the use of technology as well as integrating it in their specific disciplines: Procedure During the summer the teachers spent an intensive week using StarLogo a programming language that requires students to explore, create, design and understand the workings of complex systems and models through advanced computation and visualization. The outcome for the week was the creation of a usable model that could be integrated directly into the core curriculum during the school year. Each teacher was required to develop a dynamic model along with an appropriate lesson/curricular guide. Results
FIGURE 3: MODELING INTERACTIONS
Additionally, StarLogo provides built in collision routines, which facilitates modeling system response to feedback as seen in Figure 4.
FIGURE 4: MODELING FEEDBACK
The original design for Serendipity was modeled on the typical introductory programming course. Originally, the teachers were to get a quick overview of its features. Then they were to be instructed in basic and control commands finally GUI statements. The plan was to have the teachers create simple programs in the first couple days. They were going to build in order to get a feel for StarLogo programming. Getting the teachers to commit that first day was extremely difficult; the teachers were reluctant programmers. Given the complexity of the process they were having a very difficult time seeing why they would even want to use models in their classrooms let alone learning how to program StarLogo. Traci the Social Studies teacher remarked that “I could see maybe Monica (math) or Angie (science) using this [StarLogo] in their classrooms, but I don’t see any way that it would be useful in my classroom (social studies) ”. The primary goal of integrating dynamic models in the classroom was getting lost. This created a realization that the instructional design for Serendipity needed to be to completely reconceptualized.. The “bottom-up” approach of teaching them first how to program StarLogo and then model building was not going to work. Somehow I needed to convince the teachers that StarLogo was only one way to solve the
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Session M1H problem of creating dynamic models. Other methods were possible. During the summer of 2008 the United States was in the midst of a very important presidential election. Given that the media was airing a lot of advertising for both national and local candidates I began to think about the notion of influence. How can all of these ads convince someone to vote for any one particular candidate? From this observation I developed a conceptually simplistic model of the influence/advertising process. On the second day I dumped my original instructional design. On that day we spent most of the morning simply talking about the upcoming presidential election. Then I posed the question – How do you get someone to vote for you? – What are the elements or the behaviors? What happens when you influence your friends and they in turn influence their friends? The teachers enthusiastically suggested that influence was a matter of exposure/contact to ideas, the issues or the candidates. This easily translated into a programmable behavior such as the number of times a candidate makes contact with a potential voter. Next, I suggested that if a specific candidate can switch enough voters they would reach a tipping point where the number of supporters would cascade and the candidate wins. This approach excited Traci. She realized that using StarLogo was critical to implementing this idea. She also realized that it was easy to increase the sophistication of the model by adding more agents, which she termed the “Homer Simpson factor”. In her model there are voters who no matter how much contact was made would not be influenced. Once Traci saw that she could conceptualize a way to complete the model she could see the reason for learning how to program StarLogo as illustrated in Figure 5. From that day forward learning how to program StarLogo was taught on a “need-to-know” basis. For example the teachers would not be taught how to add a control element such as a slider to their model unless they wanted the students to be able to modify the program on the fly.
FIGURE 5: BANDWAGON EFFECT MODEL
The focus of Serendipity for the rest of the summer project was to develop the model. StarLogo facilitated the development of not only dynamic models but also the creation of epistemic discourse in the classroom. Notice in Figure 5 Traci added some control widgets that make it very easy to observe, question, test and interpret the results. Because the model is dynamic, each time it is executed, the outcomes are different. Consequently the students can tweak the model and observe different results. By the end of the summer program, the teachers had developed three content specific models: Food Web, Bandwagon and Debit or Credit. COGNITIVE SCAFFOLDING On the surface the primary barrier for Serendipity appeared to be learning how to program effectively in StarLogo. However, these teachers were not only skilled in teaching strategies but were also skilled in the content knowledge. The real barrier was having the teachers contextualize how programming was simply a means to an end. The key to success was bridging the gap. These teachers, when confronted with new technologies or skills opted to attack the problem from an operational level. From that perspective they effectively could not see “the forest for the trees”. These teachers were resistant to even conceiving of how the new skill or technology could be useful or beneficial for their core curriculum. However, providing these teachers with a context effectively scaffolded the goal so they could move past the issue of programming to creating appropriate and effective models to integrate into the middle school curriculum. Cognitive scaffolding refers to a variety of instructional techniques that defines a process where “a teacher or more knowledgeable peer provides assistance that enables learners to succeed in problems that would otherwise be too difficult” [13, p. 338]. The process includes but is not limited to modeling, providing hints and coaching techniques that allow learners to overcome barriers to solving problems. As Quintana points out “ Scaffolding can help learners accomplish tasks within their zone of proximal development by providing the assistance learners need to accomplish tasks more complex than they could do alone in such a way that they can still learn from that experience” [13, p. 340]. This has huge consequences not just for middle school teachers but any instructional situation such as computer science or engineering. By understanding the background of the students the instructor can tap into their prior knowledge in order to help them make the leap, by creating a scaffold that would bridge the gap. This has important consequences for designing effective learning activities. By incorporating the prior experience and knowledge of your learners they are less resistant to the idea of the activity. This is the notion that Ausubel [4] used in advancing his idea of the advanced organizer. By creating the condition through which learners could readily see how this new task, idea, or concept fit into their prior knowledge
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Session M1H they would more readily add the new idea or skill to their extant cognitive structure The teachers had to escape their curricular limits in seeing the value of modeling. The interesting element in this is that Traci teaches the notion of the bandwagon effect in her government class during the spring semester. Monica had a similar epiphany. She is required to explore credit issues because of the state content standards. Once we were able to bridge the gap for Traci, Monica was able to develop a very clever credit model for her students to explore. Angie seems to have had the easiest time but she also was able to expand her own knowledge by modifying the traditional scientific method to include multiple variables all interacting at the same time. The essential element was the importance of cognitive scaffolding in bridging the conceptual gap. By the simple discussion the teachers were able to see the model and to realize it in software. The middle school teachers were cautious about integrating new technologies or methods even though they were teaching in their specialties. The social studies teacher finally declared that she did not see how programming dynamic models would ever be useful in her classroom. What we did was to move the discussion from the tactical (concentrating on learning how to program using Star Logo) to the more strategic (creating discipline specific models) level of discussion. The teachers were not only able to grasp the purpose for learning about programming dynamic system models but were highly successful in implementing the new knowledge and skill in their classrooms. The teachers had to escape their tactical myopia. They had to fit the new knowledge into a conceptual framework. However, because these teachers were able to reference the correct conceptual framework they were able not only to imagine an appropriate dynamic model but were able to learn the necessary programming to create a working model. They possessed the correct prior knowledge that helped them contextualize the new skill and knowledge. All that was needed was to nudge them along the correct path until they were able to see how they could effectively integrate the new activities into their classrooms. IMPLICATIONS This study also has important implications for student outcomes. Preliminary data from using the Food Web model in an eighth grade classroom was exciting. The students as a group were curious, insightful and very engaged. Further, the development and use of the dynamic modeling can be integrated and support the core curriculum. Additionally, dynamic models in the classroom can facilitate the movement from the traditional style to one that includes more epistemic forms of discourse. Further, computer-based models are easy to implement and simple to integrate into the ongoing curriculum. What this means is that a shift to more scientific inquiry can be seamless without a tremendous amount of retooling. Given the effective design of StarLogo, targeted educational
technologies can have a dramatic impact on the quality of middle school curriculum. ACKNOWLEDGMENT Funding provided by The National Energy Technology Laboratory (NETL) Pittsburgh, PA. REFERENCES [1] Grigg, W. S., Lauko, M. A., & Brockway, D. M.. The Nation's Report Card Science 2005 (NCES 2006-466). Washington, DC: U.S Government Printing Office [2] Zimmerman, C., Raghavan, K., & Sartoris, M. L The impact of the MARS curriculum on students' ability to coordinate theory and evidence. International Journal of Science Education, 25(10), 1247-1271, 2003. [3] Hanauer, D. I, Jacobs-Sera, D., Pedulla, M. L, Cresawn, S. G, Hendrix, R.W., & Hatfull, G. F., Inquiry learning: Teaching Scientific Inquiry, Science, 314, 5807, 1880-1881,2006 [4] Novak, J. D. The Learning, Creating, and using knowledge: Concept maps as facilitative tools in schools and corporations. Lawerence Erlbaum: Mahwah, NJ 1998 [5] Chin, C., Classroom interaction in science: Teacher interaction and feedback to students’ responses. International Journal of Science Education, 28, 11, 1315-1346, 2006 [6] Ahern, T. C. Computer-mediated communication technology for language acquisition: A framework for authentic design. In F. Zhang & B. Barber (Eds.), Handbook on Computer-enhanced Language Learning.295306, (2008). [7] Roth, M-W., Art and artifact of children’s designing: A situated cognition perspective. The Journal of the Learning Sciences, 5,2, 129-166, 1996. [8] National Research Council. (1999). Introducing the National Science Education Standards. Washington, DC: National Academy of Sciences. [9] Wiseman, C. E., Adams, W. K., & Perkins, K.K., PhET: Simulations that enhance learning. Science, 322682-683. [10] Penner, D., Lehrer, R., & Schauble, L. From physical models to biomechanics: A design-based modeling approach. The Journal of the Learning Sciences, 7, 3&4, 1998 , 429-449 [11] Ahern, T.C. The effectiveness of visual programming for model building in middle school. Frontiers in Education, S3D, 9-13, 2008 [12] StarLogo TNG. Computer program. Available from education.mit.edu/starlogo-tng/ [13] U.S. Department of Education, Office of Planning, Evaluation and Policy Development, Policy and Program Studies Service, State and Local Implementation of the No Child Left Behind Act, Volume II—Teacher Quality Under NCLB: Interim Report, Washington, D.C., 2007. [14] Quintana, C., Reiser, B. J., Davis, E. A., Krajcik, J., Fretz, E., Duncan, R. G., Kyza, E., Edelson, D., & Soloway, E., A scaffolding design framework for software to support science inquiry. The Journal of the Learning Sciences, 13, 3, 337-386, 2004
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