Course planning of extension education to meet market demand by using data mining techniques - an example of Chinkuo technology university in Taiwan
This study used data mining techniques to analyze the course preferences and course completion rates of enrollees in extension education courses at a university in Taiwan. First, extension courses were classified into five broad groups. Records of enrollees in extension courses from 2000-5 were then analyzed by three data mining algorithms: Decision Tree, Link Analysis, and Decision Forest. Decision tree was used to find enrollee course preferences, Link Analysis found the correlation between course category and enrollee profession, and Decision Forest found the probability of enrollees completing preferred courses. Results will be used as a reference for curriculum development in the extension program. (c) 2006 Elsevier Ltd. All rights reserved.
extension education data mining decision tree algorithm link analysis algorithms decision forest algorithm