Teaching and learning with digital teaching platforms and immersive authentic simulations.
GUEST COLUMN | by Chris Dede
Editor’s note: The following is based on what was originally a thought piece for the U.S. Department of Education STEM Workshop March 15-16, 2015. Here we present a longer-than-usual but lucid read for your consideration. Over the last ten years, education has witnessed some transformation. In just ten years from now, there’s room for more. We hope you find Chris’ vision informative to your work in education, technology, teaching and learning. -VR
In its landmark report Education for Life and Work in the 21st Century, the National Research Council (2012) described “deeper learning” as an instructional approach important in preparing students with sophisticated cognitive, intrapersonal, and interpersonal skills. The approaches recommended by advocates of deeper learning are not new, and historically these instructional strategies have been described under a variety of terms. Until now, however, they have been rarely practiced within the nation’s high schools (Dede, 2014):
- Case-based learning helps students master abstract principles and skills through the analysis of real-world situations;
- Multiple, varied representations of concepts provide different ways of explaining complicated things, showing how those depictions are alternative forms of the same underlying ideas;
- Collaborative learning enables a team to combine its knowledge and skills in making sense of a complex phenomenon;
- Apprenticeships involve working with a mentor who has a specific real-world role and, over time, enables mastery of their knowledge and skills;
- Self-directed, life-wide, open-ended learning is based on student’s passions and connected to students’ identities in ways that foster academic engagement, self-efficacy, and tenacity;
- Learning for transfer emphasizes that the measure of mastery is application in life rather than simply in the classroom;
- Interdisciplinary studies help students see how differing fields can complement each other, offering a richer perspective on the world than any single discipline can provide;
- Personalized learning ensures that students receive instruction and supports that are tailored to their needs and responsive to their interests (US Department of Education, 2010; Software and Information Industry Association, 2010; Rose & Gravel, 2010);
- Connected learning encourages students to confront challenges and pursue opportunities that exist outside of their classrooms and campuses (Ito et al, 2013); and
- Diagnostic assessments are embedded into learning and are formative for further learning and instruction.
These entail very different teaching strategies than the familiar, lecture-based forms of instruction characteristic of industrial-era schooling, with its one-size-fits-all processing of students. Rather than requiring rote memorization and individual mastery of prescribed material, they involve in-depth, differentiated content; authentic diagnostic assessment embedded in instruction; active forms of learning, often collaborative; and learning about academic subjects linked to personal passions and infused throughout life.
New tools and media can be extremely helpful to many teachers who would otherwise struggle to provide these kinds of instruction for deeper learning (Dede, 2014). By analogy, imagine that you wish to visit a friend twenty miles away. You could walk (and some people would prefer to do so), but it would be much easier to use a bicycle, and it would far easier still to use a car. In short, teachers of STEM subjects don’t have to use educational technology; they may prefer to walk. Realistically, however, many, if not most, teachers in STEM fields will be hard-pressed to get from industrial-style instruction to deeper learning without the vehicles of digital tools, media, and experiences.
Many, if not most, teachers in STEM fields will be hard-pressed to get from industrial-style instruction to deeper learning without the vehicles of digital tools, media, and experiences.
In an extensive review of the literature on technology and teaching for the forthcoming American Educational Research Association (AERA) Handbook of Research on Teaching (5th Edition), Barry Fishman and I (Fishman & Dede, in press) note the important distinction between using technology to do conventional things better and using technology to do better things (Roschelle et al., 2000). While there may be value in doing some types of conventional instruction better (i.e., more efficiently and effectively), the real value in technology for teaching lies in rethinking the enterprise of schooling in ways that unlock powerful learning opportunities and make better use of the resources present in the 21st century world.
In our review, we consider how and under what conditions technology can be productively employed by teachers to more effectively meet the challenges presented by a rapidly evolving world. We argue that technology as a catalyst is effective only when used to enable learning with richer content, more powerful pedagogy, more valid assessments, and links between in- and out-of-classroom learning. The technologies that we examined in depth were:
- Collaboration tools, including Web 2.0 technologies and tools that support knowledge building;
- Online and hybrid educational environments, which are increasingly being used to broaden access to education, but also have the potential to shift the way we conceive of teaching and learning;
- Tools that support learners as makers and creators, which have their deep roots in helping students learn to become programmers of computers (and not just users of them);
- Immersive media that create virtual worlds to situate learning or augment the real-world with an overlay of computational information; and
- Games and simulations that are designed to enhance student motivation and learning.
If used in concert, these deeper-learning technologies can help prepare students for life and work in the 21st century, mirroring in the classroom some powerful methods of knowing and doing that pervade the rest of society. Further, they can be used to create a practical, cost-effective division of labor, one that empowers teachers to perform complex instructional tasks.
In addition, these media can address the learning strengths and preferences of students growing up in this digital age, including bridging formal instruction and informal learning. And, finally, these technologies can provide powerful mechanisms for teacher learning, by which educators deepen their professional knowledge and skills in ways that mirror the types of learning environments through which they will guide their students.
For reasons of space, this thought piece focuses on just two ways of using these technologies by 2025 to aid teaching and learning in STEM fields: digital teaching platforms and immersive authentic simulations.
DIGITAL TEACHING PLATFORMS
Digital Teaching Platforms (DTPs) are a new kind of classroom learning infrastructure enabled by advances in theory, research, and one-to-one computing initiatives (Dede & Richards, 2012). This system is designed to operate in a teacher-led classroom as the major carrier of the curriculum content and to function as the primary instructional environment. Note that DTPs are not meant to replace teachers or control their work. Attempts since the dawn of computing to build “teacher-in-a-box” instructional systems have produced only simplistic learning environments that have limited effectiveness (with the exception of intelligent tutoring systems limited to a narrow range of subject matter). As Fishman and Dede (in press) document, the focus in educational technology has appropriately turned from artificial intelligence (AI) to amplifying the intelligence of teachers and students (IA).
By 2025, a full-fledged DTP will serve three major functions: First, a DTP is a networked digital portal that includes interactive interfaces for both teachers and students. To use a DTP, each student and the teacher have a laptop, or some equivalent computational device, connected to the network. Teachers use the administrative tools of the DTP to create lessons and assignments for students and to manage and evaluate the work the students do. These capabilities include specific assessment tools, allowing teachers to create tests and other types of measures, assign them to students, and review the results. The teacher tools also provide timely reports on student progress and on their remedial needs, and the tools for students allow them to complete assignments and assessments. More important, these tools allow for both individual and group work: Some students can work independently on individualized assignments, while others work collaboratively on shared assignments.
Second, a DTP provides the content of the curriculum and assessments for teaching and learning in digital form. This content includes reading material, instructional strategies, exercises, assessments, manipulative activities, special-purpose applications, multimedia materials, and any other digital content and assessments that the teacher wishes to add.
Third, a DTP supports real-time, teacher-directed interaction in the classroom. The system includes special tools for managing classroom activity, monitoring progress on assignments, displaying student work to the entire class through an interactive whiteboard or similar device, managing group discussions, and coordinating large- and small-group activities. In short, the DTP is an assistant for all the types of instructional activities a teacher might wish to implement.
The deeper-learning capabilities of a DTP function effectively in the give-and-take atmosphere of a STEM classroom. The teacher can shift quickly from large-group demonstrations, to small-group activities, to individualized practice and assessment. Students move seamlessly from using their devices for these activities to ignoring their computers and participating in dialogues. The teacher is central in guiding student activities through giving assignments, mentoring individuals, and leading discussions.
Students move seamlessly from using their devices for these activities to ignoring their computers and participating in dialogues.
In short, DTPs offer a form of blended or hybrid learning, in which the role of providing instruction is shared by teacher and technology, leading to a mix of face-to-face and digitized student experiences.
Current Examples of STEM-related DTPs
To illustrate the potential of DTPs for deeper learning, here are three current examples.
As Linn (2012) describes, the Web-based Inquiry Science Environment (WISE), which has many characteristics of a DTP, supports students’ knowledge integration using case-based, collaborative learning in which students interpret multiple representations and are assessed through embedded diagnostics (http://wise.berkeley.edu/). WISE is designed to engage students in four specific aspects of knowledge integration: eliciting ideas, adding ideas, distinguishing ideas, and sorting out ideas. In a classroom using WISE, for example, the teacher might begin by asking students to predict the sequence of events in specific chemical reactions and then assign them to conduct virtual experiments on those chemicals, using the computer to simulate what would happen in the laboratory. (Unlike a real-world laboratory, though, WISE allows students to plug in any number of experimental conditions and variables, giving them the opportunity to try out numerous versions of the experiment and to observe and compare the differing outcomes.)
The teacher might then ask students to reassess their initial predictions in light of this new information, and to discuss and debate their evolving ideas about the given chemical processes (offering them a chance to practice the use of scientific terminology and, perhaps, to come up with personal experiences or examples that show how the science applies to the wider world). Finally, the teachers might assign the students to sort out and clarify their refined ideas by explaining them to a peer, writing a persuasive essay on a relevant topic, or creating a visual representation of the idea, such as a drawing or a concept map that illustrates what they have learned. Further, WISE includes built-in assessments and rubrics that ask students to link, connect, and distinguish their ideas, and to give evidence to support their claims.
Digital Teaching Platforms can also aid teachers in adapting instruction to meet the needs of individual students. For example, the ASSISTments system for mathematics learning—which draws from the broader ”mastery learning” model first developed in the 1970s—features an on-line assessment tool designed to spot any gaps in students’ background knowledge of a subject, so that teachers can decide precisely which skills each student will need to strengthen in order to be able to grasp new and more complicated material (http://www.assistments.org). A major challenge for the mastery learning approach has always been the amount of record keeping it requires. Teachers need to keep track of exactly which skills each student has mastered, which skills are giving them trouble, and which ones they’ll have to learn in order to move on to a new unit (Heffernan et al, 2012).
However, ASSISTments takes care of much of that record keeping, while providing a number of additional tools that help teachers to individualize instruction. For example, each problem set in ASSISTments is configured to automatically track the amount of practice students get, determining that a student has “mastered” a given skill once she is able to solve a number of problems in row, without making any errors. For students who have no trouble with the skill, the assessment is quick, letting them move on to more challenging material. For others, the built-in ASSISTments tutoring may be sufficient to help them reach mastery. Or, since the system provides ongoing reports as to which students are struggling with which skills, teachers can act in timely fashion to provide other kinds of support. Given the teacher’s hands-on involvement in assigning problems, monitoring individual student progress, and providing guidance as needed, ASSISTments is a much more effective platform for personalized instruction than are simpler “learning management systems” that merely keep track of students’ progress.
DTPs have been found to provide powerful support for collaborative learning. For example, Hegedus and Roschelle (2012) describe how SimCalc, a well-known and much-studied mathematics curriculum, is configured to enable highly engaging whole class discussions (www.kaputcenter.umassd.edu/products/curriculum_new). Since representations of student thinking and work can be rapidly distributed in a networked classroom, teachers have the opportunity to direct everyone’s attention to specific participants and their contributions. For example, when using SimCalc’s Fishy World, students each “become” a particular fish and learn how the linked graphical representation and symbolic functions relate to their and others’ movements. In order to call attention to \a particular mathematical concept, the teacher can freeze each student’s SimCalc environment, pausing the simulation for a group discussion. Or the teacher can show or hide each student’s contribution, in order to have a different kind of discussion. This form of collaborative dialogue and debate—stimulated and grounded by the technology—prepares students well for the types of mathematics they will encounter in STEM fields.
The Evolution of DTPs
Overall, these examples and findings indicate that there are many benefits to using this complementary suite of media to enable multiple dimensions of deeper learning: case-based instruction, multiple linked representations, embedded diagnostics, and collaborative knowledge building (Dede, 2014). In short, DTPs could help to solve what the U.S. National Educational Technology Plan called “a grand challenge for research and development” (2010, page 78):
Today, we have examples of systems that can recommend learning resources a person might like, learning materials with embedded tutoring functions, software that can provide….supports for any technology-based learning materials, and learning management systems that move individuals through sets of learning materials and keep track of their progress and activity. What we do not have is an integrated system that can perform all these functions dynamically while optimizing engagement and learning for all learners. Such an integrated system is essential for implementing the individualized, differentiated, and personalized learning called for in this plan. Specifically, the integrated system should be able to discover appropriate learning resources; configure the resources with forms of representation and expression that are appropriate for the learner’s age, language, reading ability, and prior knowledge; and select appropriate paths and scaffolds for moving the learner through the learning resources with the ideal level of challenge and support.
DTPs represent an important step towards achieving that vision, while simultaneously providing a means by which to scale up classroom instruction that aims at deeper learning. Indeed, it is difficult to see how most classroom teachers could (absent extraordinary personal heroism) implement the types of ambitious leaching and learning described above without support from tools and media like a DTP.
IMMERSIVE AUTHENTIC SIMULATIONS
The second type of technology for deeper learning, immersive authentic simulations, goes beyond a DTP in placing emphasis on the world outside the classroom. Experiences such as internships in 21st century workplace settings offer potential benefits for student motivation, academic learning, and mastery of skills for the global, knowledge-based, innovation-centered economy (Dede, 2012). However, providing extended, mentored real-world activities outside classrooms is difficult, particularly for younger students. Moreover, internship/apprenticeship models are hard, if not impossible, to bring to scale, partly because the number of workplace sites willing to accept mentoring responsibilities for students is limited, and partly because teachers accustomed to conventional classrooms often struggle to adapt to this form of education. Fortunately, virtual worlds and augmented realities now offer the opportunity for students to experience simulated internships in STEM fields without leaving their classrooms.
Two types of immersive media underlie a growing number of formal and informal learning experiences:
- Multiuser virtual environments (MUVEs, or “Virtual Worlds”) offer students an engaging “Alice in Wonderland” experience in which their digital avatars in a graphical, virtual context actively participate in experiences with the avatars of other participants and with computerized agents. MUVEs provide rich environments in which participants can interact with digital objects and tools, such as historical photographs or virtual microscopes (Ketelhut et al., 2010).
- Augmented reality (AR) enables students to interact—via mobile wireless devices—with virtual information, visualizations, and simulations superimposed on real-world physical landscapes. For example, while looking at a tree through a pair of AR glasses, a student might also see text describing its botanical characteristics. While walking through a neighborhood, she might call up an historical photograph, showing a 19th century image of a building layered over its current appearance. Or, for that matter, her mobile device could show her an imaginary object, such as an alien spaceship flying overhead. In short, this type of immersion infuses digital resources throughout the real world, augmenting students’ experiences and interactions (Klopfer, 2008).
By immersing students in authentic simulations, MUVEs and AR promote two deeper-learning strategies, apprenticeship-based learning and learning for transfer, that are very important for STEM education.
By immersing students in authentic simulations, multi-user virtual environments (MUVEs) and augmented reality (AR) promote two deeper-learning strategies, apprenticeship-based learning and learning for transfer, that are very important for STEM education.
The EcoMUVE middle grades curriculum teaches scientific concepts about ecosystems while engaging students in scientific inquiry (both collaborative and individual) and helping them learn complex causality (http://ecomuve.gse.harvard.edu). The curriculum consists of two MUVE-based modules, allowing students to explore realistic, 3-dimensional pond and forest ecosystems. Each module consists of ten 45-minute lessons and includes a complex scenario in which ecological change is caused by the interplay of multiple factors (Metcalf et al., 2013). Students assume the role of scientists, investigating research questions by exploring the virtual environment and collecting and analyzing data from a variety of sources over time. In the pond module, for example, students can explore the pond and the surrounding area, even venturing under the water; see realistic organisms in their natural habitats; and collect water, weather, and population data. Students visit the pond over a number of virtual “days” and eventually make the surprising discovery that, on a day in late summer, many fish in the pond have died. Students are then challenged to figure out what happened—they travel backward and forward in time to gather information to solve the mystery and understand the complex causality of the pond ecosystem.
The EcoMUVE curriculum uses a “jigsaw” pedagogy, in which students have access to differing information and experiences; they must combine their knowledge in order to understand what is causing the changes they see. Working in teams of four, students are given roles that embody specific areas of expertise (naturalist, microscopic specialist, water chemist, private investigator) and that influence how they participate and solve problems. Using the differing methods of their roles, students collect data, share it with teammates via tables and graphs that they create within the simulation, and then work collaboratively to analyze the combined data and figure out how a variety of inter-connected parts come together to produce the larger ecosystem dynamics. The module culminates with each team creating an evidence-based concept map—representing their understanding of the causal relationships at work in the ecosystem—which they present to the class.
Designed to complement EcoMUVE, the EcoMOBILE project explores the potential of augmented reality (as well as the use of data collection “probeware,” such as a digital tool that measures the amount of dissolved oxygen in water, to support learning in environmental science education (http://ecomobile.gse.harvard.edu). The EcoMOBILE curriculum is a blend of the EcoMUVE learning experiences with the use of digital tools that enhance students’ real-world activities, as illustrated by a 3-day project that has been field-tested successfully (Kamarainen et al., 2013): During one class period, a group of middle school students participated in an EcoMUVE learning quest, completing a 5–10 minute on-line simulation in which they learned about dissolved oxygen, turbidity, and pH. The following day, the students went on a field trip to a nearby pond, in order to study the relationship between biological and non-biological factors in the ecosystem, practice data collection and interpretation, and learn about the functional roles (producer, consumer, decomposer) of organisms in the life of the pond.
At a number of spots around the pond, students’ handheld devices showed them visual representations—overlaid onto the real environment—of the natural processes at work in the real environment, as well as interactive media including relevant text, images, audio, video, 3D models, and multiple-choice and open-ended questions. Students also collected water measurements using Vernier probes. On the next school day after the field trip, back in the classroom, students compiled all of the measurements of temperature, dissolved oxygen, pH, and turbidity that had been taken during the field trip. They looked at the range, mean, and variations in the measurements and discussed the implications for whether the pond was healthy for fish and other organisms. They talked about potential reasons why variation may have occurred, how these measurements may have been affected by environmental conditions, and how to explain outliers in the data. Our research shows that virtual worlds and augmented realities are powerful complements for learning in STEM fields.
The Evolution of Immersive Authentic Simulations
Overall, the evidence suggests that immersive media can be used in a number of ways to promote deeper learning, such as by facilitating case-based instruction, collaborative activities, simulated apprenticeships, and the development of scientific inquiry skills, including the collection and analysis of data to provide warrants for specific claims (Dede, 2014). Simulations allow students to learn skills under controlled conditions that may be difficult to replicate in the real world (Dawley & Dede, 2013), but which convey some degree of authenticity, allowing what is learned in one setting to transfer to the other. And Augmented Realities embed learning in the real world, giving students a deeper understanding of the immediate environment (Dunleavy & Dede, 2013). On their own, each of these approaches has important benefits for students; and blending them together presents even greater opportunities for deeper learning.
On their own, each of these approaches has important benefits for students; and blending them together presents even greater opportunities for deeper learning.
Further, researchers have only just begun to explore the ways in which immersive media might contribute to high-quality educational assessment. While participating in EcoMUVE or another simulation, for example, students generate enormous amounts of information about their motivation and engagement, efforts to collaborate with their peers, problem solving strategies, persistence, understanding of core content, and—to the extent that the simulation requires them to assess their own work, explain the strategies they pursued, and reflect on the simulation—evidence of their metacognitive development.
By 2025, DTPs and immersive authentic simulations can transform STEM learning, in and out of school.
Dawley, L., & Dede, C. (2013). Situated learning in virtual worlds and immersive simulations. In J.M. Spector, M.D Merrill, J. Elen, & M.J. Bishop (Eds.), The handbook of research on educational communications and technology (4th ed.), pp. 723-734. New York: Springer.
Dede, C. (2014). The role of technology in deeper learning. New York, NY: Jobs for the Future.
Dede, C. (2012). Interweaving assessments into immersive authentic simulations: Design strategies for diagnostic and instructional insights (Commissioned White Paper for the ETS Invitational Research Symposium on Technology Enhanced Assessments). Princeton, NJ: Educational Testing Service.
Dede, C., & Richards, J. (2012). Digital teaching platforms: Customizing classroom learning for each student. New York: Teachers College Press.
Dunleavy, M., and Dede, C. (2013). Augmented reality teaching and learning. In J.M. Spector, M.D Merrill, J. Elen, & M.J. Bishop (Eds.), The handbook of research on educational communications and technology (4th ed.), pp. 735-745. New York: Springer.
Fishman, B., & Dede, C. (in press). Teaching and technology: New tools for new times. In D. Gitomer & C. Bell (Eds.), Handbook of research on teaching, 5th edition (American Educational Research Association). New York, NY: Springer.
Heffernan, N. T., Heffernan, C. L., Decoteau, M. B., & Militello, M. (2012). Effective and meaningful use of educational technology: Three cases from the classroom. In C. Dede & J. Richards (Eds.), Digital teaching platforms: Customizing classroom learning for each student (pp. 88-102). New York, NY: Teacher’s College Press.
Hegedus, S. J., & Roschelle, J. (2012). Highly adaptive, interactive instruction: Insights for the networked classroom. In C. Dede & J. Richards (Eds.), Digital teaching platforms: Customizing classroom learning for each student (pp. 103–116). New York: Teachers College Press.
Ito, M., Gutiérrez, K., Livingstone, S., Penuel, B., Rhodes, J., Salen, K., Schor, J., Julian Sefton-Green, J., & Watkins, S.C. (2013). Connected learning: An agenda for research and design. Irvine, CA: Digital Media and Learning Research Hub.
Kamarainen, A.M., Metcalf, S., Grotzer, T., Browne, A., Mazzuca, D., Tutwiler, M.S., & Dede, C. (2013). EcoMOBILE: Integrating augmented reality and probeware with environmental education field trips. Computers & Education. Available online 14 March 2013
Ketelhut, D. J., Nelson, B. C., Clarke, J., & Dede, C. (2010). A multi-user virtual environment for building and assessing higher order inquiry skills in science. British Journal of Educational Technology, 41(1), 56–68.
Klopfer, E. (2008). Augmented learning: Research and design of mobile educational games. Cambridge, MA: MIT Press.
Linn, M. C. (2012). Insights for teaching and learning science. In C. Dede & J. Richards (Eds.), Digital teaching platforms: Customizing classroom learning for each student (pp. 55–70). New York: Teachers College Press.
Metcalf, S., Kamarainen, A., Grotzer, T., & Dede, C. (2013). Teacher perceptions of the practicality and effectiveness of immersive ecological simulations as classroom curricula. International Journal of Virtual and Personal Learning Environments, 4(3), 66-77
National Research Council (2012). Education for life and work: Developing transferable knowledge and skills in the 21st century. Washington, DC: The National Academies Press. http://www.nap.edu/catalog.php?record_id=13398
Roschelle, J. M., Pea, R. D., Hoadley, C. M., Gordin, D. N., & Means, B. M. (2000). Changing how and what children learn in school with computer-based technologies. The Future of Children: Children and Computer Technology, 10(2), 76–101.
Rose, D.H. & Gravel, J.W. (2010). Universal design for learning. In E. Baker, P. Peterson, & B. McGaw (Eds.). International Encyclopedia of Education, 3rd Ed. Oxford: Elsevier.
Software & Information Industry Association. (2010, November). Innovate to Educate: System [Re]Design for Personalized Learning; A Report from the 2010 Symposium. In collaboration with ASCD and the Council of Chief State School Officers. Washington, DC. Author: Mary Ann Wolf.
U.S. Department of Education. (2010). Transforming American education: Learning powered by technology (National Educational Technology Plan 2010). Washington, DC: Office of Educational Technology, U.S. Department of Education.
Chris Dede is the Timothy E. Wirth Professor in Learning Technology at Harvard Graduate School of Education. His fundamental interest is developing new types of educational systems to meet the opportunities and challenges of the 21st century. His research spans emerging technologies for learning, infusing technology into large-scale educational improvement initiatives, developing policies that support educational transformation, and providing leadership in educational innovation. Write to: email@example.com