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2020 | OriginalPaper | Buchkapitel

Recommender System for Quality Educational Resources

verfasst von : Wafa Bel Hadj Ammar, Mariem Chaabouni, Henda Ben Ghezala

Erschienen in: Intelligent Tutoring Systems

Verlag: Springer International Publishing

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Abstract

Current educational recommender systems (RS) represent an essential support tool and the most used system to interpret patterns and human interaction, which supports deeper learning and provides users with fast and accurate data.

In an e-learning environment supported by RS, the learner often needs additional educational resources to enrich his learning scenario to meet his needs and deepen his knowledge and skills. So he spends a lot of time identifying his need, selecting the most convenient data sources and finding the appropriate resources to the current content of his activity.

However, in the era of Big Data, apart from the services offered by RS and other data filtering tools, data sources are currently experiencing a significant evolution in terms of volume and variety of available resources. Given the importance of these data, the quality of the recommended content is decreasing significantly, which implies poor knowledge and a failed learning experience.

To enhance the quality of student’s learning, we propose an approach of recommending quality educational resources, in accordance to the learner’s learning progress and his individual needs.

The quality assessment module is integrated into the recommendation process to judge the level of quality of the resources. To help the quality assessment module make a better decision and improve analytics, we used artificial intelligence technique, Fuzzy Logic to simulate the human reasoning process and aid to deal with the uncertain data in engineering.

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Vorheriges Kapitel Validating the Reflective Writing Framework (RWF) for Assessing Reflective Writing in Computer Science Education Through Manual Annotation

Nächstes Kapitel Intelligent Tutoring Systems for Psychomotor Training – A Systematic Literature Review

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Titel: Recommender System for Quality Educational Resources
verfasst von: Wafa Bel Hadj Ammar
Mariem Chaabouni
Henda Ben Ghezala
Verlag: Springer International Publishing
Buch: Intelligent Tutoring Systems
Print ISBN: 978-3-030-49662-3

Electronic ISBN: 978-3-030-49663-0

Copyright-Jahr: 2020
DOI: https://doi.org/10.1007/978-3-030-49663-0_39

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