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.
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References
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)
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)
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)
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)
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)
Baylor, A.L., Kim, Y.: Simulating instructional roles through pedagogical agents. International Journal of Artificial Intelligence in Education 15(2), 95–115 (2005)
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)
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.2007.69
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-2010-012
Dweck, C.: Self-Theories: Their role in motivation, personality and development. Psychology Press, Philadelphia (2000)
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)
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)
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)
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)
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)
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)
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)
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/s11257-010-9086-0
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
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.2007.09.003
Weiner, B.: An attributional theory of achievement motivation and emotion. Psychological Review 92(4), 548 (1985)
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)
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)
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)
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Girard, S. et al. (2013). Defining the Behavior of an Affective Learning Companion in the Affective Meta-tutor Project. In: Lane, H.C., Yacef, K., Mostow, J., Pavlik, P. (eds) Artificial Intelligence in Education. AIED 2013. Lecture Notes in Computer Science(), vol 7926. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-39112-5_3
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DOI: https://doi.org/10.1007/978-3-642-39112-5_3
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