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Review of intelligent tutoring systems using bayesian approach

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arxiv 1302.7081 v1 pith:QSGMOQSV submitted 2013-02-28 cs.CY

classification cs.CY
keywords systemstutoringintelligentbayesiancognitivelearningnetworksresearch
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With advancement in computer science research on artificial intelligence and in cognitive psychology research on human learning and performance, the next generation of computer-based tutoring systems moved beyond the simple presentation of pages of text or graphics. These new intelligent tutoring systems (ITSs) called cognitive tutors; incorporated model-tracing technology which is a cognitive model of student problem solving that captures students multiple strategies and common misconceptions. Such Intelligent tutoring systems or Knowledge Based Tutoring Systems can guide learners to progress in the learning process at their best. This paper deals with the review of various Intelligent tutoring systems using Bayesian Networks and how Bayesian Networks can be used for efficient decision making.

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Cited by 1 Pith paper

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  1. A Comprehensive Review of AI-based Intelligent Tutoring Systems: Applications and Challenges

    cs.IR 2025-07 conditional novelty 3.0 of 10

    A systematic review of 2010-2025 intelligent tutoring systems finds promising personalization and feedback features but mixed evidence and calls for stricter experimental standards.

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