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Education and Information Technologies

Erschienen in:

05.06.2020

Personalization of study material based on predicted final grades using multi-criteria user-collaborative filtering recommender system

verfasst von: Dina Fitria Murad, Yaya Heryadi, Sani Muhamad Isa, Widodo Budiharto

Erschienen in: Education and Information Technologies | Ausgabe 6/2020

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Abstract

The recommender system has gained research attention from education research communities mainly due to two main reasons: increasing needs for personalized learning and big data availability in the education sector. This paper presents a hybrid user-collaborative, rule-based filtering recommendation system for education context. User profiles are represented by learning outcome scores and contextual information. The user-collaborative filtering method is used for predicting the targeted student’s learning outcome of a particular course. The predicted learning outcome combined with a set of decision rules are used for recommending some relevant link of learning materials to the targeted student. The initial contextual information which is assessed during the online program entrance test makes it possible for the proposed recommneder system to give automated recommendations to new students. The proposed method was tested using student learning outcome records from BINUS Online repository data. The results of performance evaluation of both recommender system with contextual information which achieves 458.22 MSE and the recommender system without contextual information which achieves 413.19 MSE are not significantly different. However, unlike the latter recommender system, the former recommender system has an advantage mainly that it can be used to give recommendation to the targeted students since their early program stage.

Vorheriger Artikel Open educational resources (OER) usage trends among university students of Pakistan

Nächster Artikel Experienced educators’ suggestions for solutions to the challenges to technology integration

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Titel: Personalization of study material based on predicted final grades using multi-criteria user-collaborative filtering recommender system
verfasst von: Dina Fitria Murad
Yaya Heryadi
Sani Muhamad Isa
Widodo Budiharto
Publikationsdatum: 05.06.2020
Verlag: Springer US
Erschienen in: Education and Information Technologies / Ausgabe 6/2020
Print ISSN: 1360-2357
Elektronische ISSN: 1573-7608
DOI: https://doi.org/10.1007/s10639-020-10238-9

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