Chapter 85
Evolving Learning Designs and Emerging Technologies Donna DeGennaro
Recent efforts have focused on how best to design learning environments that engage students in ways that emulate the activities of practicing scientists (NSTA 2003). An integral aspect of scientists’ practices includes the use of various technologies. In the profession, technology acts as a tool to support the processes by which scientists perform inquiry, carry out investigations, collect data, and execute analysis. Although productivity tools, such as spreadsheets and word processors exists as a support for the teaching and learning of science, the last several decades have introduced many emerging technologies into classrooms. These include visualizations, animations, and simulations to name a few. Each of these tools provides insight into learning designs that actively immerse students in roles that reflect those of scientists. What is more, it becomes evident that these evolving learning designs alter the roles of teachers and learners. New roles ultimately offer students a more authentic and self-directed learning experience in science classrooms. Together, the trends in science education, learning designs, and the use of technology bring about unique possibilities for the support teaching and learning of science education. This chapter presents emerging technologies and their association with evolving learning designs. To begin, I first overview the skills and dispositions projected as being crucial to science education. Following this, I offer a definition of and research trends in learning environments to assist in framing how the trends reflect the most recent research on effectively engaging students in learning science. Within this section, I present examples of technology-mediated learning environments and their interconnectedness to the design of learning experience in science education. I conclude by providing an overview of the trends and offering implications for future designs.
C. DeGennaro (*) Department of Curriculum and Teaching, University of Massachusetts, Boston, MA 02125-3393, USA e-mail:
[email protected]
B.J. Fraser et al. (eds.), Second International Handbook of Science Education, Springer International Handbooks of Education 24, DOI 10.1007/978-1-4020-9041-7_85, © Springer Science+Business Media B.V. 2012
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Trends in Science Education The major research and science organizations have offered their perspective on what it means to become scientifically literate. Namely, these organizations have generated a comprehensive array of skills and dispositions that are important for both scientific literacy (AAAS 1993) and twenty-first-century learning (The Partnership for 21st Century Learning, 2004). These two concepts suitably converge as a foundational grounding to commence our thinking about designing effective learning environments for science education. To begin, science literacy is defined by several broad components. In addition to having basic factual knowledge, students should acquire the ability to understand issues of daily scientific events found in news. An example of this might be the governmental debate around global warming. Another factor of scientific literacy is gaining an appreciation for the natural and scientific world. Part of science literacy then, is having the ability to make informed personal decisions based upon appreciating how natural laws of science influence one’s life (Hazen 2002). Collectively, these components focus on the overarching importance of scientific concepts rather than a focus on discrete facts and skills often associated with the teaching and learning of this discipline. Similarly, twenty-first-century skills include factual knowledge as well as applicable real-world skills. In the discipline of science these inevitably include content knowledge. However, content knowledge is not isolated; rather it is seen as embedded in pedagogical models such as problem-based learning, cooperative learning, and real-world contexts. The assertion is that these models offer the most effective learning designs for science education because they place students in the center of scientific practices. For example, students’ employment of creativity, innovation, critical thinking, problem solving, communication, and collaboration is intertwined within the learning design. These skills are fostered as students create research questions, develop theories, use and offer reliable explanations, and make accurate predictions. In carefully crafted learning designs, students also engage in an iterative process of building theories, asking questions, investigating, reasoning, and predicting (NRC 1996; AAAS 1993). Further, students work closely and interactively with others to inform their thinking. Experts who have crafted the twenty-first-century skills model have also projected that students should be utilizing technology as part of their learning process and as a result gain numerous technology-related skills. These include information literacy, media literacy, and ICT literacy (The Partnership for 21st Century Learning 2004). The twenty-first-century model expands the construct of scientific literacy by providing a comprehensive picture of the complex nature of becoming literate in this discipline. While a listing of skills along with an implied implementation of how they become cultivated is helpful, it falls short of illuminating a clear picture of how science and technology come together to foster scientific knowledge and practice. Too often technology has been viewed in education as a tool or a supplement to learning (Varma et al. 2008). Scientists, however, utilize emerging technologies as
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an interconnected part of their work. Research offers a more integral picture of what this might look like (Sawyer 2006). To begin this conversation, I expand the notion of learning design drawing from the learning sciences perspective. This serves as a backdrop to frame the research trends supporting how emerging technologies have become an inseparable and supportive part of the teaching and learning of science.
Learning Designs The Learning Sciences is a field dedicated to the research and development of pedagogical, technological, and social policy innovations. The aim of researchers in this field is to study the design, implementation, and evolution of designed learning environments with a goal of improving education. The focus has traditionally been on the role of social context, cognition, and design in learning. More recently, centers such as LIFE (Learning in Informal and Formal Environments) have included development, psychology, neurobiology, and sociocultural disciplines to help inform our understanding of learning. Much of the research in this field is conducted in and around how technology supports the learning of science. The learning scientists’ commitment of examining how technologies supports science learning comes, to some degree, from the realization that professions today find their work entails interpreting and accessing multiple forms and representations of information. Information presents itself through visualizations, text, numbers, images, and other graphical forms. As scientists work, they are continuously moving back and forth between different kinds of information formats to create research questions, inquire, analyze and interpret data, and make new conjectures for further study. They are also connected to a broad community of other scientists who share information and co-construct knowledge and ideas. This suggests that scientists will inevitably cross multiple boundaries of practices – across people, tools, and “texts.” We can then envision that scientists are continuously in practice with various resources around them, including working in and across the technology. In order to inform the design of learning environments, the learning sciences group has developed new research frameworks and methods to examine the multidimensional view of learning and technology within learning designs. Namely, learning scientists employ Design Experiments (Brown 1992) and Design Research (Barab 2006; Cobb et al. 2003). Analysis is focused on the orchestration of and relation between expected tasks, encouraged discourses, established norms, used tools and materials across multiple contexts. The cross-examination of the findings across local contexts informs effective design principles (Cobb et al. 2003). The research involves the voice and contribution of all participants connected to the learning environment including teachers, students, researchers, and designers. These frameworks have been criticized for not including or attending to particular aspects of the learning structure. Specifically, aspects often absent from the research include beliefs about learning and knowledge, learning activities and participant structures, configurations of both physical and virtual spaces (Bielaczyc 2006).
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With this, it is critical to examine not only the learning design outcomes, but also how the social and technical aspects of the learning design. Specifically, when students use technologies, their social participation and technology use dialectically, rather than causally, create activity (Lenk 1997). Social refers to the people. In particular, social is the knowledge, skills, attitudes, values, and needs people bring to the environment. Technical comprises of tools, devices, and techniques needed to support the transformation of inputs to outputs (Coakes 2002). The social and the technical systems act together to create the structure (Trist and Bamforth 1951) – the learning structure in this case. In what follows, I offer learning design themes with embedded emerging technologies. Within these themes, I provide several evolving examples that suggest how the social and technical aspects of the learning designs support science practice. The examination of technology-mediated learning designs as a means of fostering scientific proficiencies affords opportunities for teachers and students to learn in concert with human and material resources in unique ways.
Collaboration and Knowledge Building For many years, the technologies have supported scientific collaboration and knowledge building. These forms of participation have been a long embedded part of scientific work. As early as 1969, scientists have been connecting with others through the Internet to tap their knowledge and expertise. The connections have been crucial to scientific progress, as complex investigations of scientific questions require the expertise of more than one person. Following this model, educational designers have taken advantage of this flexibility and connectability of electronic mediums to allow students to learn in ways that are similar to those of practicing scientists. Today, Web 2.0 technologies make knowledge construction and building even more seamless and simple. The following designs provide early illustrations of how web-based tools afford the organization and sharing of information to support collaboration and knowledge building. An early attempt at collaborative software took advantage of premature Internet communications technologies such as email and newgroups. The Collaboratory Notebook (Edelson et al. 1996) was modeled loosely on the notion of a scientist’s notebook. It was part of a larger research project called CoVis (Gomez et al. 1998). Designed to support collaborative learning models, students worked with team members to post questions, share databases with team members, and have access to remote mentors (telementors). Among other scientific practices, this design model fosters collaboration and communications skills not only with students but also with real scientists. Studies found that this model was an accessible design to support iterative practices such as giving students opportunities to post, refine, and quickly receive feedback on the ongoing scientific process (Edelson et al. 1996). Although, access to telementors was difficult to sustain, the connection to real scientists gave students insights into how real scientists work and think (O’Neill et al. 1996).
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Design experiments and test bed research examining this design were used not only to see the ways in which teachers and students used them, but also how they would diversely and effectively integrate into classroom learning (Gomez et al. 1998). This effective integration encompasses the opportunities for distributed knowledge through technical supports of the discussion posts, databases, and remote access. Another example of an innovation that draws on Internet connectivity is CSILE (Computer Supported Intentional Learning Environments). CSILE is a web-based tool designed for students to interact with each other across a communal database. This online database has both text and graphic capabilities. The learning design is grounded in both a collaborative and problem-based learning. It also draws upon a Knowledge Building Environments philosophy (Scardamalia and Bereiter 2006). Knowledge Building Environments is grounded in the belief that discourse is a primary part of learning science. More specifically, it is “discourse whose aim is progress in the state of knowledge: idea improvement” (Scardamalia and Bereiter 2006, p. 102). The commitment is to engage students in collaboratively solving a proposed problem where the students learning progresses through communal collaborations. The concept is that the ongoing discussions both drawn from the databases yields common understanding and expands the base of accepted facts by that community. CSILE’s multi-window networked learning environment affords students the opportunity to work across resources (computer tools, textual and graphical resources, peers, and teachers) in order to build an understanding of scientific topics. As students work with their peers, receive guidance from the teacher, and access scientific content, they are socially constructing knowledge (Scardamalia and Bereiter 1993) similar to how scientists do. One of the key successes of knowledge building in platforms such as CSILE is that through accessing multiple forms of information with and through the technology students become a legitimate part of building knowledge together as they move in and out of core and peripheral participation (Lave and Wenger 1991). CSILE supports technical and social integration to potentially “restructure the flow of information in the classroom” (Scardamalia and Bereiter 2006, p. 104) as all participants use the technology to consult on questions, ideas, criticisms, and suggestions in a public space. One collaborative discussion model that utilizes the affordances of the Internet is Kids as Global Scientists (KGS). The learning design is based on research suggesting that student-negotiated conversations foster insight into their own knowledge (Brown and Campione 1994). KGS integrates this philosophy with an inquiry-based science model that allows geographical dispersed participants (teachers, students, and parents) to view the same data. The activity centers on investigating weather and climate concepts in one’s city. The medium also supports collaboration between students and science experts around real-time and archived weather and species datasets. In these programs, participants use the same weather data from the Internet, along with archival weather data to develop questions around the affects and influences of weather in their hometowns and across the world. Similar to the previous examples are using technical tools to formulate scientific understands and work with peers and experts to formulate questions. This process is ongoing and occurs across technologies and people.
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Co-constructing Scientific Processes Scientists are continually immersed in trying to form understandings of real-world situations. That is, they are researching current environmental phenomena for which they are attempting to find solutions. As a result, they need to be in a constant cycle of developing hypotheses, designing experiments, arguing theories, and testing solutions. This cyclical practice is not completed in isolation, nor is it done without the aid of technological tools. Various technology-enhanced learning designs have placed students in scenarios that reproduce the collective practices of developing scientific processes. For example, Biology Guided Inquiry Learning Environment (BGuILE) utilizes an inquiry-based learning model to immerse students in the midst of a scientific mystery (Sandoval and Reiser 2004). Students are presented with the fact that an inordinate number of finches in the Galapagos Islands have died during a drought. The learning goal is to gain a better understanding of popular genetics. With this goal in mind, students enter the scenario in order to solve the problem through analysis of extensive data collected and organized by real genetic scientists. While students are not collecting their own data, they are acting as scientists would when brought in as experts together to examine a problem. The students are traversing social and technical spaces by accessing authentic data and conferring with their peers to make inferences. That process of scientifically and socially constructing knowledge is made visible within a tool called Explanation Constructor. This tool prompts students to scaffold their argument-making skills. Specifically, it acts as a guide to ensure that students are engaged in a real-world scientific process of problem solving. Researchers, however, have found that interacting with these environments may not be enough to help students develop understandings and ways of communicating that are consistent with scientific views. A socio-technical system of learning needs to combine both virtual and face-to-face interactions. A balance of technically mediated learning and offline small and whole-group learning structures provide a more comprehensive and supportive learning design (Tabak and Reiser 1997). This finding emphasizes that the technology itself is not central to the design, but rather an interconnected part of the larger learning environment. Web-based Inquiry Science Environment (WISE), a free online learning environment for students in grades 5–12, is another platform that places students in the center of a problem. The WISE online database offers numerous previously designed inquiry questions from which teachers can choose. Some topics include genetically modified foods, earthquake prediction, the deformed frog mystery, and global warming. Once teachers choose an activity, students are guided through an inquiry process in order to ultimately take a position on the problem. The learning design is based on a model called SKI (Scaffolded Knowledge Integration). In this model, it is believed that inquiry must help make thinking visible, provide social supports, make science accessible, and promote autonomy for lifelong science learning (William 2008). Each learning activity begins by engaging students in questions that assist teachers in ascertaining what previous knowledge students bring to the
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assigned topic. After students reflect upon their current understandings, they are immediately connected to learning about and responding to a contemporary scientific controversy. Throughout the activity, students are continually evaluating information from predetermined websites and recording that information in an online journal. WISE has embedded tools that provide organizational supports for online investigations that model scientific processes. These tools scaffold student’s investigations, development of inquiry questions, note taking, evidence gathering, information sharing, and knowledge display (William 2008). In closing the experience, students review the information they saved within these tools, color-code themes from the data, and construct an argument based on these themes in order to design debates to support their position. WISE designs advocate a carefully balanced combination of interactions between online and offline activities. The visibility of thinking in person and through the technology equally provides teachers with ongoing insights into how students are engaging in scientific practice. Further, this immediate visibility affords teachers an opportunity to intervene immediately when misconceptions materialize or practices need to be enhanced. An alternative example of co-constructing scientific processes is evident in Learning by Design (LBD) (Kolodner 1997, 2006). LBD draws upon case-based reasoning (Schank 1982) to situate students in generating design skills, research skills, collaboration, and record-keeping skills. LBD is designed to orchestrate an iterative process of developing a hypothesis, designing an experiment and implementing that experiment. The expectation is that students learn by attempting to achieve design challenges. The design process promotes reflection on the experience needed to learn productively from this experience. SIMLE (Kolodner 2006) is a technology innovation used to assist in the fostering and support of the learning process. During the implementation of their design, students write their experiences into a Design Diary page, which later translates to an online case library for others to use. The Design Diary page scaffolds learners by providing prompts as students create designs, run experiments, and collect data. At designated points within the process, students share their data and data interpretations through poster presentations. In the process of planning, design, implementation, and redesign, students make changes based upon feedback from their presentations. This design has suggested that learners are given the opportunity to try again, often several times. Through working across technological supports and interactions with their classmates, students continuously create, revise, and recreate their designs to work toward better solutions (Kolodner 2006). The design elements cultivate a disposition of iterative processes so that students understand that scientific work is ongoing. Solutions do not present themselves upon the first try. Studies of LBD have indicated that students rely on both social and technical activities to build understandings, apply what they learn, and get real-time feedback. Yet research suggests that new iterations of LBD should place more emphasis on the in-person social aspects of the design. Learning designs must include scaffolds that equally rely on the interrelationship of social and technical interactions in the problemsolving process.
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Maneuvering Visualizations Creating and maneuvering visualizations is necessary for the development for scientific knowledge. Scientists use technology to support the creation of multidimensional visualizations with or without animation abilities. Scientists create and use visualizations to assist them in “seeing,” testing, and revealing aspects of scientific phenomenon that is often impossible because of its infinitesimally small-scale or inaccessible real-life recreation. Several examples of visualization have been applied in science classrooms. The following are a few of the technology-enhanced learning designs that utilize visualization to replicate how scientists might use visualizations to test ideas, uncover scientific events, gain insights to develop new schemes, and illustrate ideas that cannot be described verbally. WorldWatcher is used in education as a supportive scientific visualization environment for the investigation of scientific data (Edelson et al. 1999). Researchers and designers first introduced it into classrooms in April of 1996. WorldWatcher engages students in authentic practice (Edelson and Reiser 2006) by providing an accessible and supportive environment for students to explore, create, and analyze scientific data. Its goal is to allow students to have access to the same features found in the powerful, general-purpose visualization environments that scientists use. The visualization platform equips students with the support they require to learn through the use of the tools. WorldWatcher promotes distributed cognition and participant role dispersal. Student engagement in expert practice and teamwork affords the ability to link the manipulability of features and connection to data so that teams can make decisions about scientific processes, just as experts do (Gordin et al. 1994). Another visualization environment, Chemation, is an animation tool that allows learners to build molecular models and animations of chemical phenomena. Researchers analyzed Chemation’s ability to support practices of student learning including designing, interpreting and evaluating animations. They examined the impact of the practices on student understanding including the development of content knowledge. The results of research show that the learning design is best structured as including a combination of instructional practices. These include designing, interpreting, and evaluating animations. In this way students are working across virtual and real spaces to maneuver aspects of the visualization, talk about their analysis of the phenomenon, and question the animation’s validity. Viewing and interpreting animations were found to be least helpful. Students designing and creating their own animations have the greatest effect (Chang et al. 2007). Without the attention to fact checking with and distribution of ideas across peers, designing and interpreting animations do not sufficiently support understanding content or authentic scientific practice. A clear connection between the how students use the technology to interpret the science with peers motivates them to make clear connections with content.
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Interaction and Immersion Scientists use technology to reproduce influential factors of scientific events. To better understand these events, scientists have an opportunity to immerse themselves in virtual scenarios that replicate real-world occurrence. Educators have historically used models, and more recently games, to engage students in learning about real science principles. Here, games are defined as activities that in some sense include rivalries, strategies, or procedures toward a particular end. Games have increasingly become a contested and an acceptable method of learning science as well as cultivating science skills and dispositions (Shaffer et al. 2005). Games not only allow students to engage in dynamic play to develop and project identities (Gee 2003), but also afford immersion into ideological worlds and contested spaces (Squire 2006). The assertion is that these learning opportunities compel students to make critical decisions as they continue on an indeterminate journey. The following examples illustrate ways in which students oscillate between game player role and scientist role in order to participate with others. As they do so, students gain a deeper understanding of scientific concepts and processes. Simulations are one form of immersion that enhances students’ development of scientific knowledge (Meier et al. 2008). Participatory simulations are a set of roleplaying activities designed to give students insight into the evolution of complex dynamic systems. The intention of these learning designs is to have students take on different roles while making decisions or “being part” of unfolding phenomena. The expectation is that students will then gain a better command of the underlying scientific concepts. Further, students will gain a sense of the influence of their role on the system. For example, students become doctors, medical technicians, and public health experts to understand infectious diseases (Rosenbaum et al. 2007). The submersion in actively taking on and understanding multiple roles and their influence, students begin to use scientific language (contagious, exposure, symptoms, infections, incubation period, epidemiologists, epidemic, quarantining, and immunity) as part of their conversations in the learning environment (Neulight et al. 2007). Students articulate that their partaking in participatory simulations provides an authentic experience. Namely, students become part of the system as they attempt to avoid getting the disease. If students get the disease, the immediate community aims toward the goal of interacting with other roles to find out how to make each other better. Attaining these self-developed learning goals and insights required and motivated students to understand the scientific principles involved. Moreover, students share that they enjoyed the dynamics of the simulation and felt they realized how their actions affected the unfolding nature of the system (Rosenbaum et al. 2007). The social and technical aspects of the design revealed particular affordances for learning. However, researchers found that students’ misconceptions revealed themselves (Rosenbaum et al. 2007) and their biological explanations were still incomplete (Neulight et al. 2007). It is plausible then that teachers and designs must help students to make more explicit connections between activity and understanding as noted in similar research studies (Abelson 2008). Tools such as online chats or
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notebooks could be one means by which teachers can follow students’ progress, assumptions, and developing ideas. These in turn can support teachers efforts to identify misconceptions early enough to help transform the learning tasks and cultivate more scientific explanations. Multi-user Virtual Environments (MUVEs) are an increasingly desirable space in which students participate in their leisure time. These 3D spaces are seen to be valuable ways to immerse students in the teaching and learning of science. Students can interact with digital artifacts and other members of the learning environments through controlling avatars, which are personal virtual representations. Their avatars interact with each other and with programmed characters in the environments that are designed to act as cognitive scaffolds and assist with navigating problem sets. MUVEs, like Quest Altantis, require that students create rich narratives within their experiences. These help place the user in the role of antagonist, where students are acting out game-specific challenges (Barab et al. 2007). Narratives developed in conjunction with these games help students practice and develop scientific skills (Squire and Jan 2007). These designed experiences put students in “worlds” that encourage them use tools resources and tools within the environment to continue reading texts, generating meaning, debating meanings, and formulating new ideas (Squire and Jan 2007). In these worlds students develop ideologies about their world and the implications of decisions that they make. The situated (Greeno et al. 1995) nature of learning helps students make ties between goals of activity and place. Not all the participation takes place within the virtual space. Students report that they are “physically interacting with the simulated environment” (Rosenbaum et al. 2007, p. 38) but that they also interact and access resources offline to “win” the game. Affordances of the combination of virtual game and physical space structures are the creation of a hybrid or third space. These spaces are “neither completely fantastic nor completely real” (Squire and Jan 2007, p. 24) but work in concert with offline activity to provide students with a sensory experience that contributes to an authentic learning environment.
Conclusion and Implications Throughout history technology has been an integral aspect of scientific work. For scientists, technologies have had a particular purpose and are more often than not a transparent part of their daily activities. It is noticeable that over the years, educators and designers are attempting to emulate this use of technology in the teaching and learning of science. Great strides have been taken to balance learning and technology as opposed to considering technology as a layer on top of or a resource that is superfluous to learning. This evolution affords opportunities for learners to be a more active part of learning science. New learning designs that see technology as integral to learning have illustrated the importance of giving equal attention to the social and technology elements of learning. Moreover, both the social and technical are integral to assisting students in their development of scientific literacy and twenty-first-century skills.
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Throughout the advanced understanding about the nature of learning, variations of integrating technology have repeatedly highlighted how technology and social practices are essential to learning. This realization brings about particular design implications as designers of both technologies and learning seek to move forward. The implementation of technology in learning science suggests teaching and learning models that place students in the center of learning. For example, models that reflect cognitive apprenticeship are a way to illustrate scientific examples and processes for students. The technology works in various ways to do this. Technology can act as a support to providing examples, dialogue, inquiry, and visualizations. IT can afford students the opportunity to see models and interact with them. They can engage students in interesting virtual worlds with interactive and attention-grabbing elements. Technology certainly has its power for motivation and engagement. However, it is only as good as the overarching learning design that taps the equally powerful learning aspects of human interaction. In other words, technology used to support teaching and learning is only as good as the sound educational practices that accompany them. Furthermore, “Technology is most effective when it meets a need and fits naturally into the overall educational context. Absent these conditions, it can be a distraction” (Miller and Upton 2007, p. 136). The examples in this chapter represent various designs and the findings of their implementation. While the findings are not identical, they all point to a resounding theme. That is that without a balance of offline activities, the technology alone cannot support scientific literacy and twenty-first-century skills. Specifically, technical tools that support inquiry or offer simulations, for example, are not successful without group work (Lipson 2006). In groups, students draw on social resources and teacher guidance to make explicit connections between technology use and scientific content (Mayer 2004). Teachers need to help students through the use of cognitive organizers or other scaffolds to ensure that students access and select relevant material, organize it into meaningful representations so it will integrate into their exist knowledge (Mayer 2001). The technology is clearly a vehicle that assists learning, but it is the interconnected relationship between social and technical that brings about the most effective learning designs for science education.
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