Applying the Rasch Model to Evaluate the Self-Directed Online Learning Scale (SDOLS) for Graduate Students


  • Hongwei Yang University of West Florida
  • Jian Su University of Tennessee
  • Kelly D. Bradley University of Kentucky



self-directed learning, online teaching and learning, scale development, Rasch analysis


With the rapid growth of online learning and the increased attention paid to student attrition in online programs, much research has been aimed at studying the effectiveness of online education to improve students’ online learning experience and student retention. Utilizing the online learning literature as a multi-faceted theoretical framework, the study developed and employed a new survey instrument. The Self-Directed Online Learning Scale (SDOLS) was used to examine graduate student perceptions of effectiveness of online learning environments as demonstrated by their ability to take charge of their own learning, and to identify key factors in instructional design for effective improvements. The study applied the Rasch rating scale model to evaluate and validate SDOLS through a psychometric lens to establish the reliability and validity of SDOLS. Results from Rasch analysis addressed two research questions. First, evidence was found to generally support the new instrument as being psychometrically sound but three problematic items were also identified as grounds for future improvement of SDOLS. Second, the study assessed the importance of various factors as measured by the SDOLS items in contributing to students’ ability to self-manage their own online learning. Finally, the new instrument is expected to contribute to the work of various stakeholders in online education and can serve to improve students’ online learning experience and effectiveness, increase online retention rates, and reduce online dropouts.

Author Biographies

Hongwei Yang, University of West Florida

Hongwei Yang, Ph.D. is an assistant professor in the Department of Educational Research and Administration in the College of Education and Professional Studies at the University of West Florida. His scholarship is found in online teaching and learning, family science, human and animal medical care, survey research, quantitative methodology, and psychometrics.

Jian Su, University of Tennessee

Jian Su, Ph.D. is an Instructional Design Specialist in the Office of Information Technology at the University of Tennessee. Her research interests include online teaching and learning, Open Educational Resources, and digital distractions.

Kelly D. Bradley, University of Kentucky

Kelly D. Bradley, Ph.D. is Professor, Chair of Educational Policy Studies and Evaluation, and Program Chair of Research Methods in the College of Education at the University of Kentucky. Her research focuses on the application of quantitative methods and measurement, specializing in Survey Research and the Rasch model.



How to Cite

Yang, H., Su, J., & Bradley, K. D. (2020). Applying the Rasch Model to Evaluate the Self-Directed Online Learning Scale (SDOLS) for Graduate Students. The International Review of Research in Open and Distributed Learning, 21(3), 99–120.



Research Articles