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Predicting Learner Performance Using a Paired Associate Task in a Team-Based Learning Environment

  • Othalia LarueEmail author
  • Ion Juvina
  • Gary Douglas
  • Albert Simmons
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9183)

Abstract

In this paper, we use a computational cognitive model to make a priori predictions for an upcoming human study. Model predictions are generated in conditions identical to those that human participants will be placed in. Models were built in a computational cognitive architecture, which implements a theory of human cognition, ACT-R (Adaptive Control of Thought - Rational) (Anderson, 2007). The experiment contains three conditions: lecture, interactive lecture, and team-based learning (TBL). Team-based learning has been shown to improve performance compared to the classical non-interactive lecture. Our model predicted the same outcome. It also predicted that players in the TBL condition would perform better than players in the interactive lecture condition.

Keywords

Cognitive modeling Team-based learning A priori model prediction 

References

  1. 1.
    Anderson, J.R.: Interference: the relationship between response latency and response accuracy. J. Exp. Psychol. Hum. Learn. Mem. 7, 326 (1981)CrossRefGoogle Scholar
  2. 2.
    Borst, J.P., Anderson, J.R.: Using the ACT-R cognitive architecture in combination with fMRI data. In: Forstmann, B.U., Wagenmaker, E.-I. (eds.) An Introduction to Model-Based Cognitive Neuroscience. Springer, New York (2014)Google Scholar
  3. 3.
    Halverson, T., Gunzelmann, G.: Visual search versus memory in a paired associate task. In: Proceedings of the Human Factors and Ergonomics Society Annual Meeting, pp. 875–879. SAGE Publications (2011)Google Scholar
  4. 4.
    Pavlik, P.I., Anderson, J.R.: Practice and forgetting effects on vocabulary memory: an activation-based model of the spacing effect. Cogn. Sci. 29, 559–586 (2005)CrossRefGoogle Scholar
  5. 5.
    Michaelsen, L.K., Knight, A.B., Fink, L.D.: Team-based Learning: A Transformative Use of Small Groups. Greenwood Publishing Group, Westport (2004)Google Scholar
  6. 6.
    McInerney, M.J., Fink, L.D.: Team-based learning enhances long-term retention and critical thinking in an undergraduate microbial physiology course. Microbiol. Educ, 4, 3 (2003)CrossRefGoogle Scholar
  7. 7.
    Kelly, P.A., Haidet, P., Schneider, V., Searle, N., Seidel, C.L., Richards, B.F.: A comparison of in-class learner engagement across lecture, problem-based learning, and team learning using the STROBE classroom observation tool. Teach. Learn. Med. 17, 112–118 (2005)CrossRefGoogle Scholar
  8. 8.
    Carmichael, J.: Team-based learning enhances performance in introductory biology. J. Coll. Sci. Teach. 38, 54–61 (2009)Google Scholar
  9. 9.
    Kühne-Eversmann, L., Eversmann, T., Fischer, M.R.: Team-and case-based learning to activate participants and enhance knowledge: an evaluation of seminars in Germany. J. Continuing Educ. Health Prof. 28, 165–171 (2008)CrossRefGoogle Scholar
  10. 10.
    Anderson, J.R.: The Architecture of Cognition. Psychology Press, Philadelphia (2013)Google Scholar
  11. 11.
    Anderson, J.R.: How Can the Human Mind Occur in the Physical Universe?. Oxford University Press, New York (2007)CrossRefGoogle Scholar
  12. 12.
    Raaijmakers, J.G.: Spacing and repetition effects in human memory: application of the SAM model. Cogn. Sci. 27, 431–452 (2003)CrossRefGoogle Scholar
  13. 13.
    Hattie, J., Timperley, H.: The power of feedback. Rev. Educ. Res. 77, 81–112 (2007)CrossRefGoogle Scholar
  14. 14.
    Michaelsen, L.K., Sweet, M.: Team‐based learning. New directions for teaching and learning 2011, pp. 41-51 (2011) Google Scholar
  15. 15.
    O’Malley, K.J., Moran, B.J., Haidet, P., Seidel, C.L., Schneider, V., Morgan, R.O., Kelly, P.A., Richards, B.: Validation of an observation instrument for measuring student engagement in health professions settings. Eval. Health Prof. 26, 86–103 (2003)CrossRefGoogle Scholar
  16. 16.
    Clark, M.C., Nguyen, H.T., Bray, C., Levine, R.E.: Team-based learning in an undergraduate nursing course. J. Nurs. Educ. 47, 111–117 (2008)CrossRefGoogle Scholar
  17. 17.
    Dinan, F.J., Frydrychowski, V.A.: A team learning method for organic chemistry. J. Chem. Educ. 72, 429 (1995)CrossRefGoogle Scholar
  18. 18.
    Kreie, J., Headrick, R.W., Steiner, R.: Using team learning to improve student retention. Coll. Teach. 55, 51–56 (2007)CrossRefGoogle Scholar
  19. 19.
    Drummond, C.K.: Team-based learning to enhance critical thinking skills in entrepreneurship education. J. Entrepreneurship Educ. 15, 57–60 (2012)Google Scholar
  20. 20.
  21. 21.
    Büttner, P.: “Hello Java!” Linking ACT-R 6 with a Java simulation. In: Proceedings of the 10th International Conference on Cognitive Modeling, pp. 289–290. Citeseer (2010)Google Scholar
  22. 22.
    Paivio, A., Yuille, J.C., Madigan, S.A.: Concreteness, imagery, and meaningfulness values for 925 nouns. J. Exp. Psychol. 76, 1 (1968)CrossRefGoogle Scholar
  23. 23.
    Camerer, C.: Behavioral Game Theory: Experiments in Strategic Interaction. Princeton University Press, Princeton (2003)Google Scholar
  24. 24.
    Juvina, I., Lebiere, C., Gonzalez, C.: Modeling trust dynamics in strategic interaction. J. Appl. Res. Mem. Cogn. 1–31 (2014)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Othalia Larue
    • 1
    Email author
  • Ion Juvina
    • 1
  • Gary Douglas
    • 1
  • Albert Simmons
    • 1
  1. 1.Adaptive Strategic Thinking and Executive Control of Cognition and Affect (ASTECCA) LaboratoryWright State UniversityDaytonUSA

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