Customized Rule-Based Model to Identify At-Risk Students and Propose Rational Remedial Actions

Customized Rule-Based Model to Identify At-Risk Students and Propose Rational Remedial Actions

Detecting at-risk students provides advanced benefits for improving student retention rates, effective enrollment management, alumni engagement, targeted marketing improvement, and institutional effectiveness advancement. One of the success factors of educational institutes is based on accurate and...

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Bibliographic Details
Main Authors: Balqis Albreiki, Tetiana Habuza, Zaid Shuqfa, Mohamed Adel Serhani, Nazar Zaki, Saad Harous
Format: Article
Language:English
Published: MDPI AG 2021-11-01
Series:Big Data and Cognitive Computing
Subjects:
educational data mining
student evaluation
at-risk student
early detection
rule-based system
Online Access:https://www.mdpi.com/2504-2289/5/4/71

Internet

https://www.mdpi.com/2504-2289/5/4/71

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