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Journal of Science Education and Technology

, Volume 27, Issue 4, pp 369–384 | Cite as

Tangible User Interfaces and Contrasting Cases as a Preparation for Future Learning

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Abstract

In this paper, we describe an experiment that compared the use of a Tangible User Interface (physical objects augmented with digital information) and a set of Contrasting Cases as a preparation for future learning. We carried out an experiment (N = 40) with a 2 × 2 design: the first factor compared traditional instruction (“Tell & Practice”) with a constructivist activity designed using the Preparation for Future Learning framework (PFL). The second factor contrasted state-of-the-art PFL learning activity (i.e., students studying Contrasting Cases) with an interactive tabletop featuring digitally enhanced manipulatives. In agreement with prior work, we found that dyads of students who followed the PFL activity achieved significantly higher learning gains compared to their peers who followed a traditional “Tell & Practice” instruction (large effect size). A similar effect was found in favor of the interactive tabletop compared to the Contrasting Cases (small-to-moderate effect size). We discuss implications for designing socio-constructivist activities using new computer interfaces.

Keywords

Learning Collaboration Tangible User Interfaces Contrasting Cases Preparing for Future Learning 

Notes

Acknowledgements

We gratefully acknowledge grant support from the National Science Foundation (NSF) for this work through the CAREER Bifocal Modeling grant (NSF # 1055130).

Compliance with Ethical Standards

Ethical Approval

All procedures performed in studies involving human participants were in accordance with the ethical IRB (institutional review board) of Harvard and Stanford University. Informed consent was obtained from all individual participants included in the study.

Conflict of Interest

Bertrand Schneider and Paulo Blikstein declare that they have no conflict of interest.

References

  1. Blikstein, P., & Wilensky, U. (2009). An atom is known by the company it keeps: a constructionist learning environment for materials science using agent-based modeling. Int J Comput Math Learn, 14(2), 81–119.CrossRefGoogle Scholar
  2. Bransford, J. D., & Schwartz, D. L. (1999). Chapter 3: Rethinking transfer: a simple proposal with multiple implications. Review of Research in Education, 24(1), 61–100.CrossRefGoogle Scholar
  3. Cuendet, S., Dehler-Zufferey, J., Ortoleva, G., & Dillenbourg, P. (2015). An integrated way of using a tangible user interface in a classroom. International Journal of Computer-Supported Collaborative Learning, 10(2), 183–208.Google Scholar
  4. De Jong, T., & Van Joolingen, W. R. (1998). Scientific discovery learning with computer simulations of conceptual domains. Review of educational research, 68(2), 179–201.CrossRefGoogle Scholar
  5. Dillenbourg, P., & Evans, M. (2011). Interactive tabletops in education. International Journal of Computer-Supported Collaborative Learning, 6(4), 491–514.CrossRefGoogle Scholar
  6. Edwards, L. D. (1995). Microworlds as representations. In Computers and exploratory learning (pp. 127–154). Berlin Heidelberg: Springer.CrossRefGoogle Scholar
  7. Falcão, T. P., & Price, S. (2011). Interfering and resolving: how tabletop interaction facilitates co-construction of argumentative knowledge. International Journal of Computer-Supported Collaborative Learning, 6(4), 539–559.CrossRefGoogle Scholar
  8. Hayes, A. F., & Krippendorff, K. (2007). Answering the call for a standard reliability measure for coding data. Communication Methods and Measures, 1(1), 77–89.CrossRefGoogle Scholar
  9. Kapur, M. (2008). Productive failure. Cognition and Instruction, 26(3), 379–424.CrossRefGoogle Scholar
  10. Kenny, D. A., Kashy, D. A., & Cook, W. L. (2006). Dyadic data analysis. New York: Guilford Press.Google Scholar
  11. Kirschner, P. A., Sweller, J., & Clark, R. E. (2006). Why minimal guidance during instruction does not work: an analysis of the failure of constructivist, discovery, problem-based, experiential, and inquiry-based teaching. Educational Psychologist, 41(2), 75–86.CrossRefGoogle Scholar
  12. Klahr, D., & Nigam, M. (2004). The equivalence of learning paths in early science instruction: effects of direct instruction and discovery learning. Psychological Science, 15(10), 661–667.CrossRefGoogle Scholar
  13. Kynigos, C. (2007). Half-baked logo microworlds as boundary objects in integrated design. Informatics in Education-International Journal, 6, 335–358.Google Scholar
  14. O’Brien, H. L., Toms, E. G., Kelloway, E. K., & Kelley, E. (2008). Developing and evaluating a reliable measure of user engagement. Proceedings of the American Society for Information Science and Technology, 45(1), 1–10.CrossRefGoogle Scholar
  15. Olson, I. C., & Horn, M. S. (2011). Modeling on the table: agent-based modeling in elementary school with NetTango. In Proceedings of the 10th International Conference on Interaction Design and Children (pp. 189–192). ACM.Google Scholar
  16. Papert, S. (1980). Mindstorms: children, computers, and powerful ideas. New York: Basic Books, Inc.Google Scholar
  17. Piaget, J. (1928). The language and thought of the child. New York: Harcourt.Google Scholar
  18. Piper, A. M., & Hollan, J. D. (2009). Tabletop displays for small group study: affordances of paper and digital materials. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1227–1236). ACM.Google Scholar
  19. Schneider, B., & Blikstein, P. (2015). Unraveling students’ interaction around a tangible Interface using multimodal learning analytics. International Journal of Educational Data Mining, 7(3), 89–116.Google Scholar
  20. Schneider, B., & Blikstein, P. (2016). Flipping the flipped classroom: a study of the effectiveness of video lectures versus constructivist exploration using tangible user interfaces. IEEE Transactions on Learning Technologies, 9(1), 5–17.CrossRefGoogle Scholar
  21. Schneider, B., Jermann, P., Zufferey, G., & Dillenbourg, P. (2011). Benefits of a tangible interface for collaborative learning and interaction. Learning Technologies, IEEE Transactions on, 4(3), 222–232.CrossRefGoogle Scholar
  22. Schneider, B., Strait, M., Muller, L., Elfenbein, S., Shaer, O., & Shen, C. (2012). Phylo-Genie: engaging students in collaborative ‘tree-thinking’ through tabletop techniques. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 3071–3080). ACM.Google Scholar
  23. Schneider, B., Wallace, J., Pea, R., & Blikstein, P. (2013). Preparing for future learning with a tangible user interface: the case of neuroscience. IEEE Transactions on Learning Technologies, 6(2), 117–129.CrossRefGoogle Scholar
  24. Schwartz, D. L. (1995). The emergence of abstract representations in dyad problem solving. Journal of the Learning Sciences, 4(3), 321–354.CrossRefGoogle Scholar
  25. Schwartz, D. L., & Bransford, J. D. (1998). A time for telling. Cognition & Instruction, 16(4), 475–522.CrossRefGoogle Scholar
  26. Schwartz, D. L., & Martin, T. (2004). Inventing to prepare for future learning: The hidden efficiency of encouraging original student production in statistics instruction. C&I, 22(2), 129–184.Google Scholar
  27. Shaer, O., Strait, M., Valdes, C., Feng, T., Lintz, M., & Wang, H. (2011). Enhancing genomic learning through tabletop interaction. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 2817–2826). ACM.Google Scholar
  28. Skinner, B. F. (1986). Programmed instruction revisited. Phi Delta Kappan, 68(2), 103–110.Google Scholar
  29. Thille, C., Mitchell, J., & Stevens, M. (2015, September 22). What we’ve learned from MOOCs. Retrieved from https://www.insidehighered.com/views/2015/09/22/moocs-are-no-panacea-they-can-help-improve-learning-essay
  30. Tomasello, M. (1995). Joint attention as social cognition. In C. Moore & P. J. Dunham (Eds.), Joint attention: its origins and role in development (pp. 103–130). Hillsdale: Lawrence Erlbaum Associates, Inc..Google Scholar
  31. Tschan, F. (2002). Ideal cycles of communication (or cognitions) in triads, dyads, and individuals. Small Group Research, 33(6), 615–643.CrossRefGoogle Scholar
  32. Wilkerson-Jerde, M., Wagh, A., & Wilensky, U. (2015). Balancing curricular and pedagogical needs in computational construction kits: lessons from the DeltaTick project. Science Education, 99(3), 465–499.CrossRefGoogle Scholar
  33. Wise, A. F., Antle, A. N., Warren, J., May, A., Fan, M., & Macaranas, A. (2015). What kind of world do you want to live in? Positive interdependence and collaborative processes in the tangible tabletop land-use planning game Youtopia. In Proceedings of the 11th International Conference on Computer Supported Collaborative Learning—Volume 1 (pp. 236–243). International Society of the Learning Sciences.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Harvard Graduate School of EducationHarvard UniversityCambridgeUSA
  2. 2.Graduate School of EducationStanford UniversityStanfordUSA

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