An Adaptive Learning Approach for Better Retention of Learners in MOOCs-Reference-Cited by-同舟云学术

An Adaptive Learning Approach for Better Retention of Learners in MOOCs

Published:2020-03-31 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 3rd International Conference on Networking, Information Systems & Security
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Author:

El Miloud Smaili¹,Soukaina Sraidi¹,Salma Azzouzi¹,El Hassan Charaf My¹

Affiliation:

1. Informatics Systems and Optimization Laboratory (ISOLab), Ibn Tofail University- Kenitra

Publisher

ACM

Reference22 articles.

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2. Bakki A. et al. 2015. Motivation and engagement in MOOCs: How to increase learning motivation by adapting Pedagogical Scenarios? Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9307 (2015) 556--559. DOI:https://doi.org/10.1007/978-3-319-24258-3_58. Bakki A. et al. 2015. Motivation and engagement in MOOCs: How to increase learning motivation by adapting Pedagogical Scenarios? Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). 9307 (2015) 556--559. DOI:https://doi.org/10.1007/978-3-319-24258-3_58.

3. Dorigo M. et al. 2007. An Introduction to Ant Colony Optimization. IRIDIA - Technical Report. April 2006 (2007). Dorigo M. et al. 2007. An Introduction to Ant Colony Optimization. IRIDIA - Technical Report. April 2006 (2007).

4. Ant Algorithms for Discrete Optimization

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