Hybrid Filtering Recommendation System in an Educational Context: Experiment in Higher Education in Morocco

Mohammed Baidada, Khalifa Mansouri, Franck Poirier

Source Title: International Journal of Web-Based Learning and Teaching Technologies (IJWLTT)17(1)

ISSN: 1548-1093|EISSN: 1548-1107|EISBN13: 9781799893509|DOI: 10.4018/IJWLTT.294573

MLA

Baidada, Mohammed, et al. "Hybrid Filtering Recommendation System in an Educational Context: Experiment in Higher Education in Morocco." IJWLTT vol.17, no.1 2022: pp.1-17. http://doi.org/10.4018/IJWLTT.294573

APA

Baidada, M., Mansouri, K., & Poirier, F. (2022). Hybrid Filtering Recommendation System in an Educational Context: Experiment in Higher Education in Morocco. International Journal of Web-Based Learning and Teaching Technologies (IJWLTT), 17(1), 1-17. http://doi.org/10.4018/IJWLTT.294573

Chicago

Baidada, Mohammed, Khalifa Mansouri, and Franck Poirier. "Hybrid Filtering Recommendation System in an Educational Context: Experiment in Higher Education in Morocco," International Journal of Web-Based Learning and Teaching Technologies (IJWLTT) 17, no.1: 1-17. http://doi.org/10.4018/IJWLTT.294573

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Abstract

In education, the needs of learners are different in the majority of the time, as each has specificities in terms of preferences, performance and goals. Recommendation systems have proven to be an effective way to ensure this learning personalization. Already used and tested in other areas such as e-commerce, their adaptation to the educational context has led to several research studies that have tried to find the best approaches with the best expected results. This article suggests that a hybridization of recommendation systems filtering methods can improve the quality of recommendations. An experiment was conducted to test an approach that combines content-based filtering and collaborative filtering. The results proved to be convincing.