Educational Psychology Review

, Volume 26, Issue 2, pp 331–340 | Cite as

Integrating Cognitive Science and Technology Improves Learning in a STEM Classroom

  • Andrew C. Butler
  • Elizabeth J. Marsh
  • J. P. Slavinsky
  • Richard G. Baraniuk
Research into Practice

Abstract

The most effective educational interventions often face significant barriers to widespread implementation because they are highly specific, resource intense, and/or comprehensive. We argue for an alternative approach to improving education: leveraging technology and cognitive science to develop interventions that generalize, scale, and can be easily implemented within any curriculum. In a classroom experiment, we investigated whether three simple, but powerful principles from cognitive science could be combined to improve learning. Although implementation of these principles only required a few small changes to standard practice in a college engineering course, it significantly increased student performance on exams. Our findings highlight the potential for developing inexpensive, yet effective educational interventions that can be implemented worldwide.

Keywords

Education Technology Retrieval practice Spacing Feedback Transfer of learning 

Notes

Acknowledgments

The authors would like to thank Daniel Williamson, Matthew Moravec, Eva Dyer, Kevin Burleigh, and Kim Davenport for their contributions to this research. This research was supported by NSF grant no. IIS-1123617 to EJM and NSF grant no. IIS-1124535 and Google Faculty Research Award to RGB.

All authors contributed to the idea for the research. ACB and EJM designed the experiment. JPS directed the creation and implementation of the software infrastructure for OpenStax Tutor. RGB assisted in the design of OpenStax Tutor and taught the course. ACB analyzed the data and drafted the manuscript. All authors edited the manuscript. Correspondence and requests for materials and data should be addressed to ACB (andrew.butler@duke.edu).

References

  1. Anderson, J. R., Boyle, C. F., & Reiser, B. J. (1985). Intelligent tutoring systems. Science, 228, 456–462.Google Scholar
  2. Anderson, M. C., & McCulloch, K. C. (1999). Integration as a general boundary condition on retrieval-induced forgetting. Journal of Experimental Psychology: Learning, Memory, and Cognition, 25, 608–629.Google Scholar
  3. Anderson, M. C., Bjork, R. A., & Bjork, E. L. (1994). Remembering can cause forgetting: retrieval dynamics in long-term memory. Journal of Experimental Psychology: Learning, Memory, and Cognition, 20, 1063–1087.Google Scholar
  4. Armbruster, B. B., Anderson, T. H., & Ostertag, J. (1987). Does text structure/summarization instruction facilitate learning from expository text? Reading Research Quarterly, 22, 331–346.CrossRefGoogle Scholar
  5. Bransford, J. D., Brown, A. L., & Cocking, R. R. (1999). How people learn: brain, mind, experience and school. Washington, D.C.: National Academy.Google Scholar
  6. Butler, K. M., Williams, C. C., Zacks, R. T., & Maki, R. H. (2001). A limit on retrieval-induced forgetting. Journal of Experimental Psychology: Learning, Memory, and Cognition, 27, 1314–1319.Google Scholar
  7. Carpenter, S. K., Pashler, H., & Cepeda, N. J. (2009). Using tests to enhance 8th grade students’ retention of U.S. history facts. Applied Cognitive Psychology, 23, 760–771.CrossRefGoogle Scholar
  8. Cepeda, N. J., Pashler, H., Vul, E., Wixted, J. T., & Rohrer, D. (2006). Distributed practice in verbal recall tasks: a review and quantitative synthesis. Psychological Bulletin, 132, 354–380.CrossRefGoogle Scholar
  9. Clark, R. E. (1983). Reconsidering research on learning from media. Review of Educational Research, 53, 445–459.CrossRefGoogle Scholar
  10. Deslauriers, L., Schelew, E., & Wieman, C. (2011). Improved learning in a large-enrollment physics class. Science, 332, 862–864.CrossRefGoogle Scholar
  11. Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students’ learning with effective learning techniques promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14, 4–58.CrossRefGoogle Scholar
  12. Hattie, J. (2009). Visible learning: a synthesis of over 800 meta-analyses relating to achievement. London: Routledge.Google Scholar
  13. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77, 81–112.CrossRefGoogle Scholar
  14. Karpicke, J. D., & Roediger, H. L., III. (2008). The critical importance of retrieval for learning. Science, 319, 966–968.CrossRefGoogle Scholar
  15. 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, 75–86.CrossRefGoogle Scholar
  16. Kulik, J. A., & Kulik, C. C. (1988). Timing of feedback and verbal learning. Review of Educational Research, 58, 79–97.CrossRefGoogle Scholar
  17. MacLeod, M. D., & Macrae, C. N. (2001). Gone but not forgotten: the transient nature of retrieval-induced forgetting. Psychological Science, 12, 148–152.CrossRefGoogle Scholar
  18. McDaniel, M. A., Agarwal, P. K., Huelser, B. J., McDermott, K. B., & Roediger, H. L. (2011). Test-enhanced learning in a middle school science classroom: the effects of quiz frequency and placement. Journal of Educational Psychology, 103, 399–414.CrossRefGoogle Scholar
  19. Michaelsen, L. K., Knight, A. B., & Fink, L. D. (Eds.). (2002). Team-based learning: a transformative use of small groups. Westport: Praeger.Google Scholar
  20. Mullis, I. V. S., Martin, M. O., Foy, P., & Arora, A. (2012). TIMSS 2011 international results in science and mathematics. Chestnut Hill: TIMSS & PIRLS International Study Center, Boston College.Google Scholar
  21. Murray, T. (1999). Authoring intelligent tutoring systems: an analysis of the state of the art. International Journal of Artificial Intelligence in Education, 10, 98–129.Google Scholar
  22. OECD. (2010). PISA 2009 results: what students know and can do—student performance in reading, mathematics and science (volume I). Paris: OECD.Google Scholar
  23. OECD. (2012). Education at a glance 2012: OECD indicators. Paris: OECD.Google Scholar
  24. Pashler, H., Bain, P., Bottge, B., Graesser, A., Koedinger, K., McDaniel, M., et al. (2007). Organizing instruction and study to improve student learning: a practice guide (NCER 2007–2004). Washington, D.C.: National Center for Education Research, Institute of Education Sciences, U.S. Department of Education.Google Scholar
  25. Roediger, H. L., & Butler, A. C. (2011). The critical role of retrieval practice in long-term retention. Trends in Cognitive Sciences, 15, 20–27.CrossRefGoogle Scholar
  26. U.S. Department of Education. (2010). Transforming American education: learning powered by technology. Washington DC: Office of Educational Technology, National Education Technology Plan 2010.Google Scholar
  27. U.S. National Science Board. (2012). Science and engineering indicators 2012. Arlington: National Science Foundation (NSB 12–01).Google Scholar
  28. UNESCO Institute for Statistics (UIS). (2011). Global education digest 2011. Montreal: UIS.Google Scholar
  29. VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46, 197–221.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Andrew C. Butler
    • 1
  • Elizabeth J. Marsh
    • 1
  • J. P. Slavinsky
    • 2
  • Richard G. Baraniuk
    • 2
  1. 1.Department of Psychology & NeuroscienceDuke UniversityDurhamUSA
  2. 2.Department of Electrical and Computer EngineeringRice UniversityHoustonUSA

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