NotesFAQContact Us
Collection
Advanced
Search Tips
Peer reviewed Peer reviewed
Direct linkDirect link
ERIC Number: EJ1099864
Record Type: Journal
Publication Date: 2006
Pages: 15
Abstractor: As Provided
Reference Count: 9
ISBN: N/A
ISSN: ISSN-1539-3100
Behavior Analysis in Distance Education by Boosting Algorithms
Zang, Wei; Lin, Fuzong
International Journal of Distance Education Technologies, v4 n2 p57-71 Apr-Jun 2006
Student behavior analysis is an active research topic in distance education in recent years. In this article, we propose a new method called Boosting to investigate students' behaviors. The Boosting Algorithm can be treated as a data mining method, trying to infer from a large amount of training data the essential factors and their relations that influence students' academic successes. Based on the trained model, it is possible to predict students' academic successes and to assist them to adjust their learning behaviors. Among the essential factors selected by the Boosting algorithm, the analysis and comparison are conducted between on-campus students and off-campus students. More importantly, these findings are of great importance to academic administrators, faculty members, and instructional developers in order to improve the teaching modes and online courseware design.
IGI Global. 701 East Chocolate Avenue, Hershey, PA 17033. Tel: 866-342-6657; Tel: 717-533-8845; Fax: 717-533-8661; Fax: 717-533-7115; e-mail: journals@igi-global.com; Web site: http://www.igi-global.com/journals
Publication Type: Journal Articles; Reports - Descriptive
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: China