Prediction Student Performance in E-Learning Environment: Challenge and Opportunity-Reference-Cited by-同舟云学术

Prediction Student Performance in E-Learning Environment: Challenge and Opportunity

Published:2023 Issue: Volume: Page:861-867
ISSN:2367-3370
Container-title:Artificial Intelligence and Smart Environment
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Author:

Ali Hanae Aoulad,Mohamed Chrayah,Abdelhamid Bouzidi

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-26254-8_125

Reference16 articles.

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3. Rincy, T.N., Gupta, R.: Ensemble learning techniques and its efficiency in machine learning: a survey. In: 2nd International Conference on Data, Engineering and Applications (IDEA). IEEE (2020)

4. Polikar, R.: Ensemble learning. In: Zhang, C., Ma, Y. (eds.) Ensemble Machine Learning, pp. 1–34. Springer, Boston (2012). https://doi.org/10.1007/978-1-4419-9326-7_1

5. Dalipi, F., Imran, A.S., Kastrati, Z.: MOOC dropout prediction using machine learning techniques: review and research challenges. In: 2018 IEEE Global Engineering Education Conference (EDUCON). IEEE (2018)

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