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

• Main Authors: Nazir, M., Noraziah, A., Rahmah, Mokhtar
• Format: Article
• Language: English
• Published: IGI Global 2023
• Subjects: QA Mathematics; QA75 Electronic computers. Computer science; QA76 Computer software
• Online Access: http://umpir.ump.edu.my/id/eprint/38541/1/Students%E2%80%99%20Performance%20Prediction%20in%20Higher%20Education%20Using%20Multi-Agent%20Framework%20Based%20Distributed%20Data%20Mining%20Approach%20A%20review.pdf; http://umpir.ump.edu.my/id/eprint/38541/; http://10.4018/IJVPLE.328772; http://dx.doi.org/10.4018/IJVPLE.328772

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.