Identifying Causes Helps a Tutoring System to Better Adapt to Learners duringTraining Sessions
作者： Usef Faghihi , Philippe Fournier-Viger , Roger Nkambou , Pierre Poirier
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摘要: 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 users. integration Causal mechanism within CELTS allows first establish, through mix datamining algorithms, gross user group models. then uses these models find cause users' mistakes, evaluate their performance, predict future behavior, and, pedagogical knowledge mechanism, decide which tutoring intervention fits best.
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