Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review

Nazir, M. and Noraziah, A. and Rahmah, Mokhtar (2023) Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review. International Journal of Virtual and Personal Learning Environments, 13 (1). pp. 1-19. ISSN 1947-8518 (Print); 1947-8526(Online). (Published)

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DOI/Official URL: http://10.4018/IJVPLE.328772

Abstract

An effective educational program warrants the inclusion of an innovative construction that enhances the higher education efficacy in such a way that accelerates the achievement of desired results and reduces the risk of failures. Educational decision support system has currently been a hot topic in educational systems, facilitating the pupil result monitoring and evaluation to be performed during their development. In this literature survey, the authors have discussed the importance of multi-agent systems and comparative machine learning approaches in EDSS development. They explored the relationship between machine learning and multiagent intelligent systems in literature to conclude their effectiveness in student performance prediction paradigm. They used the PRISMA model for the literature review process. They finalized 18 articles published between 2014-2022 for the survey that match the research objectives.

Item Type: Article
Uncontrolled Keywords: Classification, Computational Intelligence, Distributed Data Mining, Educational Data Mining, Higher Education, Multi-Agent System, Prediction
Subjects: Q Science > QA Mathematics
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Q Science > QA Mathematics > QA76 Computer software
Faculty/Division: Institute of Postgraduate Studies
Faculty of Computing
Depositing User: Miss. Ratna Wilis Haryati Mustapa
Date Deposited: 30 Aug 2023 07:51
Last Modified: 30 Aug 2023 08:04
URI: http://umpir.ump.edu.my/id/eprint/38541
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