Automatic Detection of Learning Styles on OpenEdx Using Trace Analysis-Reference-Cited by-同舟云学术

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Automatic Detection of Learning Styles on OpenEdx Using Trace Analysis

Published:2024-08-06 Issue: Volume:4 Page:1-7
ISSN:
Container-title:2024 4th International Conference on Emerging Smart Technologies and Applications (eSmarTA)
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Author:

Chaabi Youness¹,Lekdioui Khadija²,Al-Ashmoery Yahya³

Affiliation:

1. Royal Institute of Amazigh Culture (IRCAM),Center of Computer Studies Information and Communication Systems (CEISIC),Rabat,Morocco

2. ENSC, Ibn Tofail University,SETIME Laboratory, Faculty of Science,Kenitra,Morocco

3. Faculty of Science Sana’a University,Department of Information Technology Al-Razi University, Department of Mathematics & Computer,Sana’a,Yemen

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10638789/10638835/10638881.pdf?arnumber=10638881

Reference33 articles.

1. Recommending system for digital educational resources based on learning analysis

2. Monitoring and visualizing students tracking data online learning activities (tracking in e-learning platforms) mvsa;Al-Ashmoery;International Journal of Information Technology & Management Information System (IJITMIS),2013

3. Determination of Distant Learner’s Sociological Profile Based on Fuzzy Logic and Naïve Bayes Techniques

4. Development of a Learning Analytics extension in Open edX

5. Learning analytics toolset for evaluating students’ performance in an E-learning Platform

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