Preservice teachers’ motivation profiles, self-regulation, and affective outcomes in online learning

ABSTRACT

The purpose of this study was to examine the relationship between motivation profiles and self-regulation in online students and self-regulation as a predictor of affective learning outcomes, depending on students’ motivation profiles. A total of 556 online preservice teachers participated in this study at a university in the United States of America. Cluster analyses yielded three subgroups of motivation: high, average, and low. One-way multivariate analysis of variance revealed that the degree of student self-regulation differed, depending on motivation profiles. In addition, multiple regression showed that for students with high motivation profiles, self-regulation between student and content and between student and instructor related with their affective learning outcomes, but only self-regulation between student and instructor related with affective learning outcomes for students with average and low motivation profiles. Overall, study results revealed that motivation profiles related with the online students’ self-regulation and with their affective learning outcomes as well.

KEYWORDS:

• motivation profiles
• self-regulation
• online learning
• affective learning outcomes
• cluster analysis

Disclosure statement

No potential conflict of interest was declared by the authors.

Additional information

Notes on contributors

Moon-Heum Cho

Moon-Heum Cho is an assistant professor in the Department of Instructional Design, Development & Evaluation at Syracuse University. His research interests are understanding and promoting online students’ active learning and technology integration for meaningful learning and teaching.

Jongpil Cheon

Jongpil Cheon is an associate professor in the Instructional Technology program at Texas Tech University. He is the director of the Center for Innovation in E-Learning. His research interests include implementing immersive online learning environments and investigating advanced technologies for interactive learning.

Seongmi Lim

Seongmi Lim is an assistant professor in the Department of Early Childhood, Youth, and Family Studies at Ball State University. Her research interests include enhancing preservice teachers’ online learning experiences and using technology in digital documentation.