Home > Archive > 2024 > Volume 14 Number 3 (2024) >
IJIET 2024 Vol.14(3): 362-371
doi: 10.18178/ijiet.2024.14.3.2058

Educational Video Recommender System

Mohamed Timmi1,*, Loubna Laaouina2, Adil Jeghal2, Said El Garouani3, and Ali Yahyaouy3
1. Faculty of Sciences Dhar El Mehraz, Sidi Mohamed Ben Abdellah University, Morocco
2. LISA Laboratory, National School of Applied Science Sidi Mohamed Ben Abdellah University Fez, Morocco
3. LISAC Laboratory, Faculty of Sciences Dhar El Mehraz Sidi Mohamed Ben Abdellah University Fez, Morocco
Email: mohamed.timmi@usmba.ac.ma (M.T.); loubna.laaouina@usmba.ac.ma (L.L.); adil.jeghal@usmba.ac.ma (A.J.); saidelgarouani@yahoo.fr (S.E.G.); ali.yahyaouy@usmba.ac.ma (A.Y.)
*Corresponding author

Manuscript received August 6, 2023; revised August 30, 2023; accepted September 20, 2023; published March 4, 2024

Abstract—In recent years, informal education has witnessed a significant upsurge, fueled by technological advancements and the ubiquitous availability of online educational content. Internet users, including students, researchers, and teachers, are increasingly seeking supplementary educational resources across diverse online repositories to augment their knowledge. Within this landscape, recommendation systems emerge as indispensable tools, aiding users in the discovery of pertinent resources aligned with their academic interests. This article proposes a novel recommendation methodology leveraging a hybrid approach, incorporating both Content-Based Filtering (CBF) and Collaborative Filtering (CF) algorithms. By harnessing information from a myriad of data repositories, this system excels in identifying and presenting the most relevant and desirable educational resources, with a particular focus on meeting the needs of students. This holistic approach embraces user profiles, contextual information, and supplementary data, underscoring its potential to revolutionize informal education in the digital age.

Keywords—recommendation systems, hybrid filtering, e-learning, informal education

[PDF]

Cite: Mohamed Timmi, Loubna Laaouina, Adil Jeghal, Said El Garouani, and Ali Yahyaouy, "Educational Video Recommender System," International Journal of Information and Education Technology vol. 14, no. 3, pp. 362-371, 2024.


Copyright © 2024 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).

General Information

  • ISSN: 2010-3689 (Online)
  • Abbreviated Title: Int. J. Inf. Educ. Technol.
  • Frequency: Monthly
  • DOI: 10.18178/IJIET
  • Editor-in-Chief: Prof. Dr. Steve Thatcher
  • Managing Editor: Ms. Nancy Y. Liu
  • Abstracting/ Indexing: Scopus (CiteScore 2022: 2.0), INSPEC (IET), UGC-CARE List (India), CNKI, EBSCO, Google Scholar
  • E-mail: ijiet@ejournal.net

 

Article Metrics in Dimensions