loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Ying Zhang 1 ; Samia Oussena 1 ; Tony Clark 2 and Hyeonsook Kim 2

Affiliations: 1 Thames Valley University, United Kingdom ; 2 Middlesex University, United Kingdom

Keyword(s): Data Mining, Higher Education, Student Retention, Student Intervention.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Engineering ; Data Mining ; Data Warehouses and OLAP ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Information Systems Analysis and Specification ; Knowledge Management ; Ontologies and the Semantic Web ; Organisational Issues on Systems Integration ; Sensor Networks ; Signal Processing ; Society, e-Business and e-Government ; Soft Computing ; Web Information Systems and Technologies

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.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 3.85.85.246

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
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 3: ICEIS; ISBN 978-989-8425-04-1; ISSN 2184-4992, SciTePress, pages 190-197. DOI: 10.5220/0002894101900197

@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 3: ICEIS},
year={2010},
pages={190-197},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0002894101900197},
isbn={978-989-8425-04-1},
issn={2184-4992},
}

TY - CONF

JO - Proceedings of the 12th International Conference on Enterprise Information Systems - Volume 3: ICEIS
TI - USE DATA MINING TO IMPROVE STUDENT RETENTION IN HIGHER EDUCATION - A Case Study
SN - 978-989-8425-04-1
IS - 2184-4992
AU - Zhang, Y.
AU - Oussena, S.
AU - Clark, T.
AU - Kim, H.
PY - 2010
SP - 190
EP - 197
DO - 10.5220/0002894101900197
PB - SciTePress