Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey

Zaid Shuqfa; Saad Harous

doi:10.1109/ICECTA48151.2019.8959789

Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey

Zaid Shuqfa, Saad Harous

Department of Computer Science and Software Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

10 Citations (Scopus)

Abstract

Predicting student retention is a crucial task for all stakeholders in higher education. This paper surveyed the Educational Data Mining (EDM) literature to explore the most recent methods used in building predictive models to predict student's retention, and to foresee the future trends in different context of higher education. We review a diversified set of approaches, models, data sets, tools, techniques, and performance measures. The approaches vary as the educational context varies where opportunities and challenges are associated with each approach. We also present a discussion and a foresight of future directions.

Original language	English
Title of host publication	2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781728155326
DOIs	https://doi.org/10.1109/ICECTA48151.2019.8959789
Publication status	Published - Nov 2019
Event	2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019 - Ras Al Khaimah, United Arab Emirates Duration: Nov 19 2019 → Nov 21 2019

Publication series

Name	2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019

Conference

Conference	2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019
Country/Territory	United Arab Emirates
City	Ras Al Khaimah
Period	11/19/19 → 11/21/19

Keywords

EDM
Educational Data Mining
Learning Analytics
Prediction
Predictive Models
Retention
Student Success

ASJC Scopus subject areas

Artificial Intelligence
Computer Science Applications
Software
Energy Engineering and Power Technology
Electrical and Electronic Engineering
Computer Networks and Communications

Access to Document

10.1109/ICECTA48151.2019.8959789

Cite this

Shuqfa, Z., & Harous, S. (2019). Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey. In 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019 Article 8959789 (2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICECTA48151.2019.8959789

Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey. / Shuqfa, Zaid; Harous, Saad.
2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. 8959789 (2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shuqfa, Z & Harous, S 2019, Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey. in 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019., 8959789, 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019, Institute of Electrical and Electronics Engineers Inc., 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019, Ras Al Khaimah, United Arab Emirates, 11/19/19. https://doi.org/10.1109/ICECTA48151.2019.8959789

Shuqfa Z, Harous S. Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey. In 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019. Institute of Electrical and Electronics Engineers Inc. 2019. 8959789. (2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019). doi: 10.1109/ICECTA48151.2019.8959789

Shuqfa, Zaid ; Harous, Saad. / Data Mining Techniques Used in Predicting Student Retention in Higher Education : A Survey. 2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019. Institute of Electrical and Electronics Engineers Inc., 2019. (2019 International Conference on Electrical and Computing Technologies and Applications, ICECTA 2019).

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Data Mining Techniques Used in Predicting Student Retention in Higher Education: A Survey

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