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ERIC Number: EJ735876
Record Type: Journal
Publication Date: 2004-May
Pages: 19
Abstractor: Author
ISBN: N/A
ISSN: ISSN-0361-0365
What Satisfies Students?: Mining Student-Opinion Data with Regression and Decision Tree Analysis
Thomas, Emily H.; Galambos, Nora
Research in Higher Education, v45 n3 p251-269 May 2004
To investigate how students' characteristics and experiences affect satisfaction, this study uses regression and decision tree analysis with the CHAID algorithm to analyze student-opinion data. A data mining approach identifies the specific aspects of students' university experience that most influence three measures of general satisfaction. The three measures have different predictors and cannot be used interchangeably. Academic experiences are influential. In particular, faculty preparedness, which has a well-known relationship to student achievement, emerges as a principal determinant of satisfaction. Social integration and pre-enrollment opinions are also important. Campus services and facilities have limited effects, and students' demographic characteristics are not significant predictors. Decision tree analysis reveals that social integration has more effect on the satisfaction of students who are less academically engaged.
Springer. 233 Spring Street, New York, NY 10013. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-348-4505; e-mail: service-ny@springer.com; Web site: http://www.springerlink.com.
Publication Type: Journal Articles; Reports - Evaluative
Education Level: Higher Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A