Applying the rasch model to evaluate the self-directed online learning scale (SDOLS) for graduate students

Hongwei Yang, Jian Su, Kelly D. Bradley

Research output: Contribution to journalArticlepeer-review

5 Scopus citations


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.

Original languageEnglish
Pages (from-to)99-120
Number of pages22
JournalInternational Review of Research in Open and Distance Learning
Issue number3
StatePublished - 2020

Bibliographical note

Publisher Copyright:
© 2020, Athabasca University.


  • Online teaching and learning
  • Rasch analysis
  • Scale development
  • Self-directed learning

ASJC Scopus subject areas

  • Education


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