Modeling learner affect with theoretically grounded dynamic Bayesian networks

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 6974 LNCS, Issue PART 1, 2011, Pages 286-295

  Sabourin, Jennifer ^a   Mott, Bradford ^a   Lester, James C ^a  

^a North Carolina State University   (United States)

Author keywords

Affective modeling; Dynamic Bayesian networks; Intelligent tutoring systems

Indexed keywords

AFFECTIVE MODELING; AFFECTIVE STATE; CRYSTAL ISLANDS; DYNAMIC BAYESIAN NETWORK; DYNAMIC BAYESIAN NETWORKS; GAME-BASED LEARNING; GENERAL MODEL; INTELLIGENT TUTORING SYSTEM; PREDICTIVE MODELS; TEMPORAL INFORMATION; THEORETICAL FOUNDATIONS; THEORETICAL MODELS;

COMPUTER AIDED INSTRUCTION; DISTRIBUTED PARAMETER NETWORKS; INFERENCE ENGINES; INTELLIGENT COMPUTING; INTELLIGENT NETWORKS; KNOWLEDGE BASED SYSTEMS; PREDICTIVE CONTROL SYSTEMS;

BAYESIAN NETWORKS;

EID: 80054834164     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-24600-5_32     Document Type: Conference Paper

References (22)

1. Conati, C., Maclaren, H.: Empirically Building and Evaluating a Probabilistic Model of User Affect. User Modeling and User-Adapted Interaction 19(3), 267-303 (2010)
2. Burleson, W.: Affective Learning Companions: Strategies for Empathetic Agents with Real-Time Multimodal Affective Sensing to Foster Meta-Cognitive and Meta-Affective Approaches to Learning, Motivation and Perseverance. PhD thesis, Massachusetts Institute of Technology (2006)
3. McQuiggan, S., Lee, S., Lester, J.: Early Prediction of Student Frustration. In: Paiva, A.C.R., Prada, R., Picard, R.W. (eds.) ACII 2007. LNCS, vol. 4738, pp. 698-709. Springer, Heidelberg (2007)
4. Marsella, S., Gratch, J.: EMA: A Process Model of Appraisal Dynamics. Cognitive Systems Research 10(1), 70-90 (2009)
5. Paiva, A., Dias, J., Sobral, D., Aylett, R., Sobreperez, P., Woods, S., Zoll, C., Hall, L.: Caring for Agents and Agents that Care: Building Empathetic Relations with Synthetic Agents. In: Proc. of the 3rd Intl. Joint Conf. on Autonomous Agents and Multiagent Systems, pp. 194-201 (2004)
6. de Vicente, A., Pain, H.: Informing the Detection of Students' Motivational State: An Empirical Study. In: Cerri, S.A., Gouardéres, G., Paraguaçu, F. (eds.) ITS 2002. LNCS, vol. 2363, pp. 933-943. Springer, Heidelberg (2002)
7. Beal, C., Lee, H.: Creating a Pedagogical Model That Uses Student Self Reports of Motivation and Mood yo Adapt ITS Instruction. In: AIED 2005 Workshop on Motivation and Affect in Educational Software (2005)
8. Kort, B., Reilly, R., Picard, R.: An Affective Model of Interplay Between Emotions and Learning: Reengineering Educational Pedagogy - Building a Learning Companion. In: Proc. IEEE Intl. Conf. on Advanced Learning Technology: Issues, Achievements and Challenges. IEEE Computer Society, Madison (2001)
9. Picard, R., Papert, S., Bender, W., Blumberg, B., Breazeal, C., Cavallo, D., Machover, T., Resnick, M., Roy, D., Strohecker, C.: Affective Learning - A Manifesto. BT Technology Journal, 22(4) (2004)
10. Arroyo, I., Cooper, D., Burleson, W., Woolf, B., Muldner, K., Christopherson, R.: Emotion Sensors Go to School. In: Proc. of the 14th Intl. Conf. on Artificial Intelligence in Education, pp. 17-24 (2009)
11. D'Mello, S., Graesser, A.: Multimodal Semi-Automated Affect Detection from Conversational Cues, Gross Body Language, and Facial Features. User Modeling and User-Adapted Interaction 20(2), 147-187 (2010)
12. 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)
13. Ortony, A., Clore, G., Collins, A.: The Cognitive Structure of Emotions. Cambridge University Press, Cambridge (1990)
14. Craig, S., Graesser, A., Sullins, J., Gholson, B.: Affect and Learning: An Exploratory Look Into the Role of Affect in Learning with AutoTutor. Journal of Educational Media 29, 241-250 (2004)
15. Csikszentmihalyi, M.: Finding Flow: The Psychology of Engagement with Everyday Life. Basic Books, New York (1997)
16. Elliot, A., McGregor, H.: A 2x2 Achievement Goal Framework. Journal of Personality and Social Psychology 80(3), 501-519 (2001)
17. Elliot, A., Pekrun, R.: Emotion in the Hierarchical Model of Aproach-Avoidance Achievement Motivation. In: Schutz, P., Pekrun, R. (eds.) Emotion in Education, pp. 57-74. Elsevier, London (2007)
18. McCrae, R., Costa, P.: Personality in Adulthood: A Five-Factor Theory Perspective, 2nd edn. Guilford Press, New York (1993)
19. Gernefski, N., Kraaij, V.: Cognitive Emotion Regulation Questionnaire: Development of a Short 18-Item Version (CERQ-Short). Personality and Individual Differences 41, 1045-1053 (2006)
20. Russell, S., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn. Pearson, London (2003)
21. Robison, J., McQuiggan, S., Lester, J.: Evaluating the Consequences of Affective Feedback in Intelligent Tutoring Systems. In: Proc. of the Intl. Conf. on Affective Computing and Intelligent Interaction, pp. 37-42 (2009)
22. Baker, R.S., D'Mello, S.K., Rodrigo, M.M.T., Graesser, A.C.: Better to Be Frustrated than Bored: The Incidence, Persistence, and Impact of Learners' Cognitive-Affective States during Interactions with Three Different Computer-Based Learning Environments. Intl. Journal of Human-Computer Studies 68(4), 223-241 (2010)