Validation of the self-regulated online learning questionnaire

Oct 25, 2016·
Renée Jansen
,
Anouschka van Leeuwen
,
Jeroen Janssen
,
Liesbeth Kester
Marco Kalz
Marco Kalz
· 1 min read
Abstract
The number of students engaged in Massive Open Online Courses (MOOCs) is increasing rapidly. Due to the autonomy of students in this type of education, students in MOOCs are required to regulate their learning to a greater extent than students in traditional, face-to-face education. However, there is no questionnaire available suited for this online context that measures all aspects of self-regulated learning (SRL). In this study, such a questionnaire is developed based on existing SRL questionnaires. This is the self-regulated online learning questionnaire. Exploratory factor analysis (EFA) on the first dataset led to a set of scales differing from those theoretically defined beforehand. Confirmatory factor analysis (CFA) was conducted on a second dataset to compare the fit of the theoretical model and the exploratively obtained model. The exploratively obtained model provided much better fit to the data than the theoretical model. All models under investigation provided better fit when excluding the task strategies scale and when merging the scales measuring metacognitive activities. From the results of the EFA and the CFA it can be concluded that further development of the questionnaire is necessary.
Type
Publication
Journal of Computing in Higher Education, 29(1), 6-27. Springer
publications publications

Jansen, R. S., Van Leeuwen, A., Janssen, J., Kester, L., & Kalz, M. (2017). Validation of the self-regulated online learning questionnaire. Journal of Computing in Higher Education, 29(1), 6-27. https://doi.org/10.1007/s12528-016-9125-x

Self-Regulated Learning Online Learning Open Education Questionnaire Development MOOCS
Marco Kalz
Authors
Marco Kalz
Professor of Educational Technology

I am a researcher in educational technology whose work explores how digital technologies reshape learning, teaching, and educational institutions. My research combines educational technology, learning sciences, feedback research, and critical perspectives on digital transformation.Current areas of interest include peer feedback and feedback literacy, open and networked learning, AI and misinformation in education, digital learning ecologies, and the societal implications of data-driven and platform-based education. Methodologically, my work spans empirical learning research, psychometric scale development, design-oriented research, and conceptual analyses of digital transformation in education.

I am working as a full professor of educational technology and Chief Information/Chief Digital Officer (CIO/CDO) at the Heidelberg University of Education. I serve as associate editor of the International Journal of Artificial Intelligence in Education and editorial board member of the Journal of Computing in Higher Education. I am a senior-fellow of the Interuniversity Center for Educational Sciences (ICO) and the Dutch research school on information and knowledge systems (SIKS). I work as director of the study program E-Learning and Media Education and director of the Heidelberg Centre for Digital Transformation in Education. Over the years I could secure approx. 4 Mio EUR of research funding for my institutions from competitive projects with a total budget of 36 Mio EUR. I have been an invited keynote speaker on more than 60 conferences and events. Besides European projects I am regularly involved in educational innovation and consulting projects with partners inside and outside of my institutions including clients like the International Labour Organisation, United Nations Environment Program, the European Commission, UNESCO, OECD or other international and national organizations.