Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
388969 | Expert Systems with Applications | 2008 | 7 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Tai-Chang Hsia, An-Jin Shie, Li-Chen Chen,