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Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning

Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning

Shweta, Praveen Dhyani, O. P. Rishi
Copyright: © 2018 |Pages: 28
ISBN13: 9781522556435|ISBN10: 1522556435|EISBN13: 9781522556442
DOI: 10.4018/978-1-5225-5643-5.ch037
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MLA

Shweta, et al. "Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning." Intelligent Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2018, pp. 901-928. https://doi.org/10.4018/978-1-5225-5643-5.ch037

APA

Shweta, Dhyani, P., & Rishi, O. P. (2018). Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning. In I. Management Association (Ed.), Intelligent Systems: Concepts, Methodologies, Tools, and Applications (pp. 901-928). IGI Global. https://doi.org/10.4018/978-1-5225-5643-5.ch037

Chicago

Shweta, Praveen Dhyani, and O. P. Rishi. "Agent-Based Distributed Intelligent Tutoring System Using Case-Based Reasoning." In Intelligent Systems: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 901-928. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5643-5.ch037

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Abstract

Intelligent Tutoring Systems have proven their worth in multiple ways and in multiple domains in education. In this chapter, the proposed Agent-Based Distributed ITS using CBR for enhancing the intelligent learning environment is introduced. The general architecture of the ABDITS is formed by the three components that generally characterize an ITS: the Student Model, the Domain Model, and the Pedagogical Model. In addition, a Tutor Model has been added to the ITS, which provides the functionality that the teacher of the system needs. Pedagogical strategies are stored in cases, each dictating, given a specific situation, which tutoring action to make next. Reinforcement learning is used to improve various aspects of the CBR module: cases are learned and retrieval and adaptation are improved, thus modifying the pedagogical strategies based on empirical feedback on each tutoring session. The student modeling is a core component in the development of proposed ITS. In this chapter, the authors describe how a Multi-Agent Intelligent system can provide effective learning using Case-Based Student Modeling.

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