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Bug Model Based Intelligent Recommender System with Exclusive Curriculum Sequencing for Learner-Centric Tutoring

Ninni Singh, Neelu Jyothi Ahuja

Source Title: International Journal of Web-Based Learning and Teaching Technologies (IJWLTT)14(4)

ISSN: 1548-1093|EISSN: 1548-1107|EISBN13: 9781522564058|DOI: 10.4018/IJWLTT.2019100101

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MLA

Singh, Ninni, and Neelu Jyothi Ahuja. "Bug Model Based Intelligent Recommender System with Exclusive Curriculum Sequencing for Learner-Centric Tutoring." IJWLTT vol.14, no.4 2019: pp.1-25. http://doi.org/10.4018/IJWLTT.2019100101

APA

Singh, N. & Ahuja, N. J. (2019). Bug Model Based Intelligent Recommender System with Exclusive Curriculum Sequencing for Learner-Centric Tutoring. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 14(4), 1-25. http://doi.org/10.4018/IJWLTT.2019100101

Chicago

Singh, Ninni, and Neelu Jyothi Ahuja. "Bug Model Based Intelligent Recommender System with Exclusive Curriculum Sequencing for Learner-Centric Tutoring," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) 14, no.4: 1-25. http://doi.org/10.4018/IJWLTT.2019100101

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Abstract

Face to face human tutoring in classroom environments amply facilitates human tutor-learner interactions wherein the tutor gets opportunity to exercise his cognitive intelligence to understand learner's pre-knowledge level, learning pattern, specific learning difficulties, and be able to offer course content well-aligned to the learner's requirements and tutor in a manner that best suits the learner. Reaching this level in an intelligent tutoring system is a challenge even today given the advanced developments in the field. This article focuses on ITS, mimicking a human tutor in terms of providing a curriculum sequence exclusive for the learner. Unsuitable courseware disorients the learner and thus degrades the overall performance. A bug model approach has been used for curriculum design and its re-alignment as per requirements and is demonstrated through a prototype tutoring recommender system, SeisTutor, developed for this purpose. The experimental results indicate an enhanced learning gain through a curriculum recommender approach of SeisTutor as opposed to its absence.

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Bug Model Based Intelligent Recommender System with Exclusive Curriculum Sequencing for Learner-Centric Tutoring

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