Journal Published Online: 02 January 2019
Volume 48, Issue 6

Mining the Student Dropout in Higher Education

CODEN: JTEVAB

Abstract

Higher technological and vocational education (TVE) has served an important role in the long-term progress and industrial development of Taiwan. However, the high dropout rates in higher TVE are a challenging task for policy makers. This study is a first to propose a hybrid approach that combines both k-means and rough set theory for mining the dropout knowledge among student dropout. An empirical case of student dropout is based on the industrial-academic cooperation (IAC) education of higher TVE in Taiwan. The results of knowledge extraction from the proposed approach are illustrated as knowledge patterns/rules and clusters to provide better understanding of the reasons for or factors influencing student dropout.

Author Information

Hsu, Ching-Wen
Department of Business Administration, National Taipei University of Business, Zhongzheng District, Taipei, Taiwan (Republic of China)
Yeh, Ching-Chiang
Department of Business Administration, National Taipei University of Business, Zhongzheng District, Taipei, Taiwan (Republic of China)
Pages: 13
Price: $25.00
Related
Reprints and Permissions
Reprints and copyright permissions can be requested through the
Copyright Clearance Center
Details
Stock #: JTE20180021
ISSN: 0090-3973
DOI: 10.1520/JTE20180021