Abstract
Predicting students’ emotion raises several questions about the data on which these predictions should be grounded. This article describes an empirical evaluation of a cognitive-based affective user model accomplished with 7th grade students. The affective model is based on the OCC psychological theory of emotions in order to infer the students’ emotions from their actions and choices in the interface of the learning system. The model relies on a BDI model to implement the process of inference of students’ emotions in a web-based learning environment. Two experiments were conducted based on a direct and an indirect approach. The results of the evaluation are discussed and some ideas of improvement for the experiments protocol are presented.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Calvo, R., D’Mello, S.: Affect Detection: An Interdisciplinary Review of Models, Methods, and Their Applications. IEEE Transactions on Affective Computing 1, 18–37 (2010)
Wehrle, T., Kaiser, S.: Emotion and Facial Expression. In: Paiva, A. (ed.) IWAI 1999. LNCS, vol. 1814, pp. 49–63. Springer, Heidelberg (2000)
Picard, R.W., Vyzas, E., Healey, J.: Toward Machine Emotional Intelligence. IEEE Transactions Pattern Analysis and Machine Intelligence 23, 1175–1191 (2001)
Martinho, C., Machado, I., Paiva, A.: A Cognitive Approach to Affective User Modeling. In: Paiva, A. (ed.) IWAI 1999. LNCS, vol. 1814, pp. 64–75. Springer, Heidelberg (2000)
Conati, C., Maclare, H.: Evaluating A Probabilistic Model of Student Affect. In: Lester, J.C., Vicari, R.M., Paraguaçu, F. (eds.) ITS 2004. LNCS, vol. 3220, pp. 55–66. Springer, Heidelberg (2004)
Jaques, P.A., Viccari, R.M.: A BDI approach to infer student s emotions in an intelligent learning environment. Computers & Education 49, 360–384 (2007)
Ortony, A., Clore, G., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press, Cambridge (1988)
Eyharabide, V., et al.: An Ontology for Predicting Students’ Emotions During a Quiz. In: IEEE Symposium Series on Computational Intelligence- Paris (2011)
Conati, C.: How to evaluate models of user affect? In: André, E., Dybkjær, L., Minker, W., Heisterkamp, P. (eds.) ADS 2004. LNCS (LNAI), vol. 3068, pp. 288–300. Springer, Heidelberg (2004)
Jaques, P.A., Lehmann, M., Pesty, S.: Evaluating the Affective Tactics of an Emotional Pedagogical Agent. In: ACM Symposium on Applied Computing, vol. 1. ACM, Hawaii (2009)
Ames, C.: Motivation: What teachers should know. Teachers College Record. 91, 409–421 (1990)
Pintrich, P.: A Manual for the Use of the Motivated Strategies for Learning Questionnaire. The Reg. of the University of Michigan (1991)
Meece, J., McColskey, W.: Improving Student Motivation (2001)
Móra, M.C., Lopes, J.G., Viccari, R.M., Coelho, H.: BDI Models and Systems: Reducing the Gap. In: International Workshop on Agent Theories, Architectures, and Languages (1998)
Rao, A.S., Georgeff, M.: BDI Agents: from Theory to Practice. Australian Artificial Intelligence Institute, Melbourne, Australia (1995)
Burleson, W., Picard, R.W.: Gender-Specific Approaches to Developing Emotionally Intelligent Learning Companions. IEEE Intelligent Systems 22, 62–69 (2007)
Silveira, R.A., Vicari, R.M.: Developing distributed intelligent learning Environment with JADE. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 105–118. Springer, Heidelberg (2002)
Sebe, N., Cohen, I., Gevers, T., Huang, T.S.: Multimodal Approaches for Emotion Recognition: A Survey. In: Internet Imaging VI. EUA, San Jose (2005)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Jaques, P.A., Vicari, R., Pesty, S., Martin, JC. (2011). Evaluating a Cognitive-Based Affective Student Model. In: D’Mello, S., Graesser, A., Schuller, B., Martin, JC. (eds) Affective Computing and Intelligent Interaction. ACII 2011. Lecture Notes in Computer Science, vol 6974. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24600-5_63
Download citation
DOI: https://doi.org/10.1007/978-3-642-24600-5_63
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-24599-2
Online ISBN: 978-3-642-24600-5
eBook Packages: Computer ScienceComputer Science (R0)