Predicting Retention in Online General Education Courses
- 1 March 2005
- journal article
- Published by Taylor & Francis Ltd in American Journal of Distance Education
- Vol. 19 (1), 23-36
- https://doi.org/10.1207/s15389286ajde1901_3
Abstract
A classification rule was developed to predict undergraduate students& withdrawal from or completion of fully online general education courses. A multivariate technique, predictive discriminant analysis (PDA), was used. High school grade point average and SAT mathematics score were shown to be related to retention in the online university courses. Locus of control and financial aid were able to identify dropout and completion with 74.5% accuracy.Keywords
This publication has 13 references indexed in Scilit:
- Some Problems in Reporting Use of Discriminant AnalysesThe Journal of Experimental Education, 2003
- Persistence of Adult Learners in Distance EducationAmerican Journal of Distance Education, 2002
- DEVELOPING AND IMPLEMENTING LOCAL-LEVEL RETENTION STUDIES: A CHALLENGE FOR COMMUNITY COLLEGE INSTITUTIONAL RESEARCHERSCommunity College Journal of Research and Practice, 2002
- Comparing Linear Discriminant Function With Logistic Regression for the Two-Group Classification ProblemThe Journal of Experimental Education, 1999
- Statistical Practices of Educational Researchers: An Analysis of their ANOVA, MANOVA, and ANCOVA AnalysesReview of Educational Research, 1998
- Discriminant Analysis in Higher Education ResearchHigher Education: Handbook of Theory and Research, 1998
- Identifying predictors of high risk among community college telecourse studentsAmerican Journal of Distance Education, 1991
- Predicting Underachievement in Business StatisticsEducational and Psychological Measurement, 1990
- Psychology: Psychological factors and distance educationAmerican Journal of Distance Education, 1990
- A Longitudinal-Process Model of Drop-Out from Distance EducationThe Journal of Higher Education, 1989