Measuring self-regulated learning in OOE

In open online education (OOE), learners are provided with a lot of autonomy: they get to decide what they want to study, where they want to study, and when they want to study. The autonomy is one of the major selling points of online education, but it also is a major challenge for learners. They have to actively take control of their own learning process to be successful. This means that they have to engage in self-regulated learning (SRL). Self-regulated learners are actively involved in their own learning process, not only during learning, but also before and after learning. Besides engaging in cognitive learning activities (e.g., rehearsal, organizing information), they also have to engage in metacognitive and resource management activities. Metacognitive activities are for instance planning, strategy regulation, and reflection. Resource management activities include time management, environmental structuring, and persistence.

Engagement in SRL activities is known to be a necessity for learners to be successful in online education. Until now, however, there was no instrument to measure learners’ SRL in OOE. In order to study SRL in OOE it was therefore important to develop such an instrument. The article describing the development and validation of this questionnaire is available open access.

We first compared several existing SRL questionnaires. None of them were directly suitable for use in OOE, but by combining items and slightly adapting them, they were used as input for the development of our questionnaire. Data was then gathered to conduct exploratory factor analysis. Hereby, we established how items should best be divided over questionnaire scales purely from a statistical perspective. Of course, we also had a theoretical division of items over questionnaire scales in mind. We next gathered data in a second MOOC. We then compared the division of items that was found with explorative analysis to the theoretical division created beforehand. We compared the questionnaires based on so-called model fit statistics, which indicate which division of items over scales best fits the data. The explorative model fitted the data best.

In the article, the resulting questionnaire is presented as the Self-regulated Online Learning Questionnaire (SOL-Q). The questionnaire can be used to measure learners’ self-reported SRL in online education, thereby allowing researchers to study SRL in OOE. It consists of five scales: metacognitive skills, time management, environmental structuring, help seeking, and persistence.

For more information about the development and the validation of the SOL-Q, and the full questionnaire, I refer you to the article which can be accessed at

CC BY 4.0 This work is licensed under a Creative Commons Attribution 4.0 International License.

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