Review: Causal knowledge and reasoning by cognitive maps: Pursuing a holistic approach
Expert Systems with Applications: An International Journal
Predictive student model supported by fuzzy-causal knowledge and inference
Expert Systems with Applications: An International Journal
Intelligent and Adaptive Educational-Learning Systems: Achievements and Trends
Intelligent and Adaptive Educational-Learning Systems: Achievements and Trends
PKAW'12 Proceedings of the 12th Pacific Rim conference on Knowledge Management and Acquisition for Intelligent Systems
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We apply activity theory (AT) to design adaptive e-learning systems (AeLS). AT is a framework to study human's behavior at learning; whereas, AeLS enhance students' apprenticeship by the personalization of teaching-learning experiences. AeLS depict users' traits and predicts learning outcomes. The approach was successfully tested: Experimental group took lectures chosen by the anticipation AT principle; whilst, control group received randomly selected lectures. Learning achieved by experimental group reveals a correlation quite significant and high positive; but, for control group the correlation it is not significant and medium positive. We conclude: AT is a useful framework to design AeLS and provide student-centered education.