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

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...

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Main Authors: Nazir, M., Noraziah, A., Rahmah, Mokhtar
Format: Article
Language:en
Published: IGI Global 2023
Subjects:
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
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author Nazir, M.
Noraziah, A.
Rahmah, Mokhtar
author_facet Nazir, M.
Noraziah, A.
Rahmah, Mokhtar
author_sort Nazir, M.
building UMPSA Library
collection Institutional Repository
content_provider Universiti Malaysia Pahang Al-Sultan Abdullah
content_source UMPSA Institutional Repository
continent Asia
country Malaysia
description 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.
format Article
id my.ump.umpir.38541
institution Universiti Malaysia Pahang
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publishDate 2023
publisher IGI Global
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spelling my.ump.umpir.385412023-08-30T08:04:10Z http://umpir.ump.edu.my/id/eprint/38541/ Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review Nazir, M. Noraziah, A. Rahmah, Mokhtar QA Mathematics QA75 Electronic computers. Computer science QA76 Computer software 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. IGI Global 2023-01 Article PeerReviewed pdf en cc_by 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 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) http://10.4018/IJVPLE.328772 http://dx.doi.org/10.4018/IJVPLE.328772
spellingShingle QA Mathematics
QA75 Electronic computers. Computer science
QA76 Computer software
Nazir, M.
Noraziah, A.
Rahmah, Mokhtar
Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title_full Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title_fullStr Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title_full_unstemmed Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title_short Students’ Performance Prediction in Higher Education Using Multi-Agent Framework-Based Distributed Data Mining Approach: A Review
title_sort students’ performance prediction in higher education using multi-agent framework-based distributed data mining approach: a review
topic QA Mathematics
QA75 Electronic computers. Computer science
QA76 Computer software
url 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
url_provider http://umpir.ump.edu.my/