Adaptive recommendation system using machine learning algorithms for predicting student’s best academic program
Author:
Publisher
Springer Science and Business Media LLC
Subject
Library and Information Sciences,Education
Link
http://link.springer.com/content/pdf/10.1007/s10639-019-10049-7.pdf
Reference28 articles.
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3. Altujjar, Y., Altamimi, W., & Al-Turaiki, I. (2016). Predicting critical courses affecting students performance: A case study. Procedia Computer Science, 82, 65–71.
4. Asif, R., Merceron, A., Abbas Ali, S., & Ghani Haider, N. (2017). Analyzing undergraduate students’ performance using educational data mining. Computers & Education, 113, 177e194.
5. Chena, J.-F., & Hung Doa, Q. (2014). A cooperative Cuckoo Search – Hierarchical adaptive neuro-fuzzy inference system approach for predicting student academic performance. Journal of Intelligent & Fuzzy Systems, 27, 2551–2561.
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