The Self-Efficacy Questionnaire for Online Learning (SeQoL)

ABSTRACT

The purpose of this study was to examine the psychometric properties of the Self-Efficacy Questionnaire for Online Learning (SeQoL; Shen et al., 2013). Using two samples of college students, this study examined evidence of construct validity, concurrent validity, convergent validity, and reliability for the SeQoL. Confirmatory factor analysis and latent profiles analysis were conducted to provide different aspects of construct validity evidence. Our results suggest the SeQoL consistently measures the five dimensions of online learning self-efficacy found in Shen et al.’s original study. We flagged five items from the original scale for further examination. In the current study, strong construct validity and reliability evidence were observed across two different samples, analytical approaches, and related measures. Online learners with higher online learning self-efficacy were found to have higher learning satisfaction and expect better grades. Interpretations and implications of the findings are discussed.

Keywords:

• online learning self-efficacy
• validity and reliability
• latent variable models
• college students

Disclosure statement

No potential conflict of interest was declared by the authors.

Additional information

Notes on contributors

Chia-Lin Tsai

Chia-Lin Tsai is an assistant professor in the Department of Applied Statistics and Research Methods at the University of Northern Colorado. Her research interests include validity studies of research instruments and online teaching and learning.

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 promoting online students’ active learning and technology integration for meaningful learning and teaching.

Rose Marra

Rose M. Marra, PhD, is a professor and director of the School of Information Science and Learning Technologies in the College of Education at the University of Missouri. Dr. Marra has 25 years’ experience in higher education, and her research areas include meaningful online learning, and STEM education.

Demei Shen

Demei Shen earned her PhD in the School of Information Science and Learning Technologies from the University of Missouri. Her research interests include the cognitive process in an online learning environment.