Providing Dynamic Instructional Adaptation in Programming Learning

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Abstract

This paper describes an approach to create an Intelligent Tutoring System that provides dynamic personalization and learning activities sequencing adaptation by combining eLearning standards and Artificial Intelligent techniques. The work takes advantage of the functionalities provided by an open source Learning Management System, dotLRN, which supports eLearning standards such as IMS-LD, and generates personalized sequences of learning activities. Moreover, the user model draws on standards such as IMS-LIP and IMS-AccLIP and the personalized learning path provided to the user is enriched with feedback coming from various Agents. In turn, the agents apply Fuzzy Logic to evaluate the students’ assignments and to update the user model with their preferences by means of machine learning techniques.