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Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

Trace Learners Clustering to Improve Learning Object Recommendation in Online Education Platforms

Author 1: Zriaa Rajae
Author 2: Amali Said
Author 3: El Faddouli Nour-eddine

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Digital Object Identifier (DOI) : 10.14569/IJACSA.2022.0130681

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 6, 2022.

  • Abstract and Keywords
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Abstract: E-learning platforms propose pedagogical pathways where learners are invited to mobilize their autonomy to achieve the learning objectives. However, some learners face a set of cognitive barriers that require additional learning objects to progress in the course. A mediating recommendation system is one of the efficient solutions to reinforce the resilience of online platforms, while suggesting learning objects that will be interesting for them according to their needs. The objective of this contribution is to design a new mediator recommendation model for e-learning platforms to suggest learning objects to the learner based on collaborative filtering. To this end, the proposed system relies on the implicit behaviors estimation function as an underlying technique to convert tacit traces into explicit preferences allowing to compute the similarity between learners.

Keywords: e-learning; recommendation system; learning objects; tacit behaviors

Zriaa Rajae, Amali Said and El Faddouli Nour-eddine, “Trace Learners Clustering to Improve Learning Object Recommendation in Online Education Platforms” International Journal of Advanced Computer Science and Applications(IJACSA), 13(6), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130681

@article{Rajae2022,
title = {Trace Learners Clustering to Improve Learning Object Recommendation in Online Education Platforms},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130681},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130681},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {6},
author = {Zriaa Rajae and Amali Said and El Faddouli Nour-eddine}
}


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