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This paper describes a computational model for the implementation of causal learning in cognitive agents. The Conscious Emotional Learning Tutoring System CELTS is able to provide dynamic fine-tuned assistance to users. The integration of a Causal Learning mechanism within CELTS allows CELTS to first establish, through a mix of datamining algorithms, gross user group models. CELTS then uses these models to find the cause of users- mistakes, evaluate their performance, predict their future behavior, and, through a pedagogical knowledge mechanism, decide which tutoring intervention fits best.

KEYWORDS

Cognitive Agents, Computational Causal Modeling and Learning, Emotions

Cite this paper

U. Faghihi, P. Fournier-Viger, R. Nkambou and P. Poirier -Identifying Causes Helps a Tutoring System to Better Adapt to Learners during Training Sessions,- Journal of Intelligent Learning Systems and Applications, Vol. 3 No. 3, 2011, pp. 139-154. doi: 10.4236-jilsa.2011.33016.





Autor: Usef Faghihi, Philippe Fournier-Viger, Roger Nkambou, Pierre Poirier

Fuente: http://www.scirp.org/



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