Defining the Behavior of an Affective Learning Companion in the Affective Meta-tutor Project

  • Sylvie Girard
  • Maria Elena Chavez-Echeagaray
  • Javier Gonzalez-Sanchez
  • Yoalli Hidalgo-Pontet
  • Lishan Zhang
  • Winslow Burleson
  • Kurt VanLehn
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7926)

Abstract

Research in affective computing and educational technology has shown the potential of affective interventions to increase student’s self-concept and motivation while learning. Our project aims to investigate whether the use of affective interventions in a meta-cognitive tutor can help students achieve deeper modeling of dynamic systems by being persistent in their use of meta-cognitive strategies during and after tutoring. This article is an experience report on how we designed and implemented the affective intervention. (The meta-tutor is described in a separate paper.) We briefly describe the theories of affect underlying the design and how the agent’s affective behavior is defined and implemented. Finally, the evaluation of a detector-driven categorization of student behavior, that guides the agent’s affective interventions, against a categorization performed by human coders, is presented.

Keywords

affective computing affective learning companion intelligent tutoring system robust learning meta-cognition 

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Arroyo, I., Ferguson, K., Johns, J., Dragon, T., Meheranian, H., Fisher, D., et al.: Repairing disengagement with non-invasive interventions. Frontiers in Artificial Intelligence and Applications, vol. 158, p. 195 (2007)Google Scholar
  2. 2.
    Arroyo, I., Woolf, B.P., Cooper, D.G., Burleson, W., Muldner, K.: The Impact of Animated Pedagogical Agents on Girls’ and Boys’ Emotions, Attitudes, Behaviors and Learning. In: Proceedings of the 2011 IEEE 11th International Conference on Advanced Learning Technologies. Proceedings from ICALT 2011, Washington, DC, USA (2011)Google Scholar
  3. 3.
    Baker, R.S.J.d., et al.: Adapting to when students game an intelligent tutoring system. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 392–401. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  4. 4.
    Baker, R.S.J.d., Gowda, S.M., Corbett, A.T.: Towards predicting future transfer of learning. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds.) AIED 2011. LNCS, vol. 6738, pp. 23–30. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  5. 5.
    Baker, R.S.J.d., Gowda, S.M., Corbett, A.T., Ocumpaugh, J.: Towards automatically detecting whether student learning is shallow. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 444–453. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  6. 6.
    Baylor, A.L., Kim, Y.: Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education 15(2), 95–115 (2005)Google Scholar
  7. 7.
    Bickmore, T.W., Picard, R.W.: Establishing and maintaining long-term human-computer relationships. ACM Transactions on Computer-Human Interaction (TOCHI) 12(2), 293–327 (2005)CrossRefGoogle Scholar
  8. 8.
    Burleson, W., Picard, R.W.: Gender-Specific Approaches to Developing Emotionally Intelligent Learning Companions. IEEE Intelligent Systems 22(4), 62–69 (2007), doi:10.1109/MIS.2007.69CrossRefGoogle Scholar
  9. 9.
    D’Mello, S.K., Lehman, B., Person, N.: Monitoring affect states during effortful problem solving activities. International Journal of Artificial Intelligence in Education 20(4), 361–389 (2010), doi:10.3233/JAI-2010-012Google Scholar
  10. 10.
    Dweck, C.: Self-Theories: Their role in motivation, personality and development. Psychology Press, Philadelphia (2000)Google Scholar
  11. 11.
    Girard, S., Zhang, L., Hidalgo-Pontet, Y., VanLehn, K., Burleson, W., Chavez-Echeagary, M.E., Gonzalez-Sanchez, J.: Using HCI task modeling techniques to measure how deeply students model. In: Chad Lane, H., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS (LNAI), vol. 7926, pp. 766–769. Springer, Heidelberg (2013)Google Scholar
  12. 12.
    Gulz, A.: Benefits of Virtual Characters in Computer Based Learning Environments: Claims and Evidences. International Journal of Artificial Intelligence in Education 14(3), 313–334 (2004)Google Scholar
  13. 13.
    Gulz, A., Haake, M., Silvervarg, A.: Extending a teachable agent with a social conversation module – effects on student experiences and learning. In: Biswas, G., Bull, S., Kay, J., Mitrovic, A. (eds.) AIED 2011. LNCS, vol. 6738, pp. 106–114. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  14. 14.
    Hayashi, Y.: On pedagogical effects of learner-support agents in collaborative interaction. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 22–32. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  15. 15.
    Katz, S., Connelly, J., Wilson, C.: Out of the lab and into the classroom: An evaluation of reflective dialogue in Andes. In: Proceeding of the 2007 Conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work, pp. 425–432 (2007)Google Scholar
  16. 16.
    Kim, Y., Baylor, A., Shen, E.: Pedagogical agents as learning companions: the impact of agent emotion and gender. Journal of Computer Assisted Learning 23(3), 220–234 (2007)CrossRefGoogle Scholar
  17. 17.
    Lehman, B., D’Mello, S., Graesser, A.: Interventions to regulate confusion during Learning. In: Cerri, S.A., Clancey, W.J., Papadourakis, G., Panourgia, K. (eds.) ITS 2012. LNCS, vol. 7315, pp. 576–578. Springer, Heidelberg (2012)CrossRefGoogle Scholar
  18. 18.
    Muldner, K., Burleson, W., Van de Sande, B., VanLehn, K.: An analysis of students’ gaming behaviors in an intelligent tutoring system: predictors and impacts. User Modeling and User-Adapted Interaction 21(1-2), 99m–135m (2011), doi:10.1007/s11257-010-9086-0Google Scholar
  19. 19.
    Rodrigo, M.M.T., Baker, R.S.J.d., Agapito, J., Nabo, J., Repalam, M.C., Reyes, S.S., San Pedro, M.O.C.Z.: The Effects of an Interactive Software Agent on Student Affective Dynamics while Using an Intelligent Tutoring System. IEEE Transactions on Affective Computing 3, 224–236 (2012), doi:http://doi.ieeecomputersociety.org/10.1109/T-AFFC.2011.41 CrossRefGoogle Scholar
  20. 20.
    Wang, N., Johnson, W.L., Mayer, R.E., Rizzo, P., Shaw, E., Collins, H.: The politeness effect: Pedagogical agents and learning outcomes. International Journal of Human-Computer Studies 66(2), 98–112 (2008), doi:10.1016/j.ijhcs.2007.09.003CrossRefGoogle Scholar
  21. 21.
    Weiner, B.: An attributional theory of achievement motivation and emotion. Psychological Review 92(4), 548 (1985)CrossRefGoogle Scholar
  22. 22.
    Walonoski, J.A., Heffernan, N.T.: Prevention of off-task gaming behavior in intelligent tutoring systems. In: Ikeda, M., Ashley, K.D., Chan, T.-W. (eds.) ITS 2006. LNCS, vol. 4053, pp. 722–724. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  23. 23.
    Woolf, B.P., Arroyo, I., Muldner, K., Burleson, W., Cooper, D.G., Dolan, R., Christopherson, R.M.: The Effect of Motivational Learning Companions on Low Achieving Students and Students with Disabilities. In: Aleven, V., Kay, J., Mostow, J. (eds.) ITS 2010, Part I. LNCS, vol. 6094, pp. 327–337. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  24. 24.
    Zhang, L., Burleson, W., Chavez-Echeagaray, M.E., Girard, S., Gonzalez-Sanchez, J., Hidalgo-Pontet, Y., VanLehn, K.: Evaluation of a meta-tutor for constructing models of dynamic systems. In: Chad Lane, H., Yacef, K., Mostow, J., Pavlik, P. (eds.) AIED 2013. LNCS (LNAI), vol. 7926, pp. 666–669. Springer, Heidelberg (2013)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Sylvie Girard
    • 1
  • Maria Elena Chavez-Echeagaray
    • 1
  • Javier Gonzalez-Sanchez
    • 1
  • Yoalli Hidalgo-Pontet
    • 1
  • Lishan Zhang
    • 1
  • Winslow Burleson
    • 1
  • Kurt VanLehn
    • 1
  1. 1.Computing, Informatics, and Decision Systems EngineeringArizona State UniversityTempeU.S.A.

Personalised recommendations