Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques

Predicting the students’ performance has become a challenging task due to the increas ing amount of data in educational systems. In keeping with this, identifying the factors afecting the students’ performance in higher education, especially by using predictive data mining techniques, is still in sh...

وصف كامل

محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Abu Saa, Amjed (author)
مؤلفون آخرون: Al‑Emran, Mostafa (author), Shaalan, Khaled (author)
منشور في: 2019
الموضوعات:
الوصول للمادة أونلاين:https://bspace.buid.ac.ae/handle/1234/2784
https://doi.org/10.1007/s10758-019-09408-7.
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author Abu Saa, Amjed
author2 Al‑Emran, Mostafa
Shaalan, Khaled
author2_role author
author
author_facet Abu Saa, Amjed
Al‑Emran, Mostafa
Shaalan, Khaled
author_role author
dc.creator.none.fl_str_mv Abu Saa, Amjed
Al‑Emran, Mostafa
Shaalan, Khaled
dc.date.none.fl_str_mv 2019
2025-02-10T05:30:30Z
2025-02-10T05:30:30Z
dc.identifier.none.fl_str_mv Abu Saa, A., Al-Emran, M. and Shaalan, K. (2019) “Factors Affecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques,” Technology, Knowledge and Learning, 24(4), pp. 567–598.
2211-1662, 2211-1670
https://bspace.buid.ac.ae/handle/1234/2784
https://doi.org/10.1007/s10758-019-09408-7.
dc.language.none.fl_str_mv en
dc.publisher.none.fl_str_mv Springer
dc.relation.none.fl_str_mv Technology, Knowledge and Learningv24 n4 (201912): 567-598
dc.subject.none.fl_str_mv Educational data mining · Students’ performance · Data mining techniques · Systematic review
dc.title.none.fl_str_mv Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
dc.type.none.fl_str_mv Article
description Predicting the students’ performance has become a challenging task due to the increas ing amount of data in educational systems. In keeping with this, identifying the factors afecting the students’ performance in higher education, especially by using predictive data mining techniques, is still in short supply. This feld of research is usually identifed as educational data mining. Hence, the main aim of this study is to identify the most com monly studied factors that afect the students’ performance, as well as, the most common data mining techniques applied to identify these factors. In this study, 36 research articles out of a total of 420 from 2009 to 2018 were critically reviewed and analyzed by applying a systematic literature review approach. The results showed that the most common fac tors are grouped under four main categories, namely students’ previous grades and class performance, students’ e-Learning activity, students’ demographics, and students’ social information. Additionally, the results also indicated that the most common data mining techniques used to predict and classify students’ factors are decision trees, Naïve Bayes classifers, and artifcial neural networks.
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identifier_str_mv Abu Saa, A., Al-Emran, M. and Shaalan, K. (2019) “Factors Affecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques,” Technology, Knowledge and Learning, 24(4), pp. 567–598.
2211-1662, 2211-1670
language_invalid_str_mv en
network_acronym_str budr
network_name_str The British University in Dubai repository
oai_identifier_str oai:bspace.buid.ac.ae:1234/2784
publishDate 2019
publisher.none.fl_str_mv Springer
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spelling Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining TechniquesAbu Saa, AmjedAl‑Emran, MostafaShaalan, KhaledEducational data mining · Students’ performance · Data mining techniques · Systematic reviewPredicting the students’ performance has become a challenging task due to the increas ing amount of data in educational systems. In keeping with this, identifying the factors afecting the students’ performance in higher education, especially by using predictive data mining techniques, is still in short supply. This feld of research is usually identifed as educational data mining. Hence, the main aim of this study is to identify the most com monly studied factors that afect the students’ performance, as well as, the most common data mining techniques applied to identify these factors. In this study, 36 research articles out of a total of 420 from 2009 to 2018 were critically reviewed and analyzed by applying a systematic literature review approach. The results showed that the most common fac tors are grouped under four main categories, namely students’ previous grades and class performance, students’ e-Learning activity, students’ demographics, and students’ social information. Additionally, the results also indicated that the most common data mining techniques used to predict and classify students’ factors are decision trees, Naïve Bayes classifers, and artifcial neural networks.Springer2025-02-10T05:30:30Z2025-02-10T05:30:30Z2019ArticleAbu Saa, A., Al-Emran, M. and Shaalan, K. (2019) “Factors Affecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques,” Technology, Knowledge and Learning, 24(4), pp. 567–598.2211-1662, 2211-1670https://bspace.buid.ac.ae/handle/1234/2784https://doi.org/10.1007/s10758-019-09408-7.enTechnology, Knowledge and Learningv24 n4 (201912): 567-598oai:bspace.buid.ac.ae:1234/27842026-01-29T15:03:07Z
spellingShingle Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
Abu Saa, Amjed
Educational data mining · Students’ performance · Data mining techniques · Systematic review
title Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
title_full Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
title_fullStr Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
title_full_unstemmed Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
title_short Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
title_sort Factors Afecting Students’ Performance in Higher Education: A Systematic Review of Predictive Data Mining Techniques
topic Educational data mining · Students’ performance · Data mining techniques · Systematic review
url https://bspace.buid.ac.ae/handle/1234/2784
https://doi.org/10.1007/s10758-019-09408-7.