A systematic literature review on adaptive content recommenders in personalized learning environments from 2015 to 2020

Author:

Raj Nisha S.ORCID,Renumol V. G.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Education

Reference85 articles.

1. Aeiad, E., & Meziane, F. (2019). An adaptable and personalized E-learning system applied to computer science Programmes design. Education and Information Technologies, 24(2), 1485–1509.

2. Aguilar, J., Valdiviezo-Díaz, P., & Riofrio, G. (2017). A general framework for intelligent recommender systems. Applied Computing and Informatics, 13(2), 147–160.

3. Al Abri, A., Jamoussi, Y., AlKhanjari, Z., & Kraiem, N. (2020). PerLCol: A framework for personalized e-learning with social collaboration support. International Journal of Computing and Digital Systems, 9(03).

4. Albatayneh, N. A., Ghauth, K. I., & Chua, F. F. (2018). Utilizing learners’ negative ratings in semantic content-based recommender system for e-learning forum. Journal of Educational Technology & Society, 21(1), 112–125.

5. Anuradha, M., Ganesan, V., Oliver, S., Jayasankar, T., & Gopi, R. (2020). Hybrid firefly with differential evolution algorithm for multi agent system using clustering based personalization. Journal of Ambient Intelligence and Humanized Computing, 1–10.

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