USE DATA MINING TO IMPROVE STUDENT RETENTION IN HIGHER EDUCATION - A Case Study

Ying Zhang, Samia Oussena, Tony Clark, Hyeonsook Kim

2010

Abstract

Data mining combines machine learning, statistics and visualization techniques to discover and extract knowledge. One of the biggest challenges that higher education faces is to improve student retention (National Audition Office, 2007). Student retention has become an indication of academic performance and enrolment management. Our project uses data mining and natural language processing technologies to monitor student, analyze student academic behaviour and provide a basis for efficient intervention strategies. Our aim is to identify potential problems as early as possible and to follow up with intervention options to enhance student retention. In this paper we discuss how data mining can help spot students ‘at risk’, evaluate the course or module suitability, and tailor the interventions to increase student retention.

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Paper Citation


in Harvard Style

Zhang Y., Oussena S., Clark T. and Kim H. (2010). USE DATA MINING TO IMPROVE STUDENT RETENTION IN HIGHER EDUCATION - A Case Study . In Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-8425-04-1, pages 190-197. DOI: 10.5220/0002894101900197

in Bibtex Style

@conference{iceis10,
author={Ying Zhang and Samia Oussena and Tony Clark and Hyeonsook Kim},
title={USE DATA MINING TO IMPROVE STUDENT RETENTION IN HIGHER EDUCATION - A Case Study},
booktitle={Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2010},
pages={190-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002894101900197},
isbn={978-989-8425-04-1},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - USE DATA MINING TO IMPROVE STUDENT RETENTION IN HIGHER EDUCATION - A Case Study
SN - 978-989-8425-04-1
AU - Zhang Y.
AU - Oussena S.
AU - Clark T.
AU - Kim H.
PY - 2010
SP - 190
EP - 197
DO - 10.5220/0002894101900197