An Experimental Study of Self-regulated Learning Strategies Application in Moocs
By: Shu-Yi Hsu
Publisher: [publisher not identified]
Published: 2021
Place of publication: [New York, N.Y.?]
Language: eng
Description: Online learning has been widely adopted in higher education to reach students who typically would not have a chance to complete accredited courses (Kentnor, 2015). Massive open online courses (MOOC), which is a type of online learning, makes it easier for people to take university courses with internet access and a fraction of cost compared to traditional residential programs (Reich, 2020). MOOCs also become popular for those who want to increase their professional profile or advance their academic career (Pheatt, 2017). However, online learning has long been criticized for its universally low completion rates, high dropout rate and poor learning performance (Almeda et al., 2018). This phenomenon is more exacerbated in MOOC environments. Historical studies have attempted to support learner self-regulated learning (SRL) activities in order to enhance completion rates and academic outcomes. Prior studies have conducted pre-course questionnaires as inexpensive SRL interventions to prompt learners as SRL support(Kizilcec et al., 2017, Kizilcec & Cohen, 2017; Kizilcec et al., 2020; Yeomans & Reich, 2017).

Yet, these one-time-only, short-term interventions only yield limited or no effects. This study implemented and evaluated the effectiveness of an alternative intervention, the self-regulated learning user interface (SRLUI), to support students' self-regulated learning (SRL) strategies in a MOOC environment. SRLUI is based on Zimmerman’s (2000) SRL model and develops learner’s SRL skills through longitudinal, recurring practice of multiple SRL dimensions activities (i.e., goal setting, self-evaluation, task planning, setting reminders) with content-specific information. The study utilized a randomized experimental design and implemented SRLUI in eight MOOCs with a total of 808 participants. The results indicated a higher usage rate of SRL support compared to the historical findings, which may be owing to the SRL support embedded into the learning activities throughout the course. Also, the study showed improved learning outcomes for a subgroup of participants, but there was no reduction in the number of dropouts.

Based on the findings of this study, it is recommended that a personalized SRL tool featuring content-specific information should be embedded in online courses. The research design also recorded direct cognitive records of learners' SRL activities, which yield stronger validity compared to trace and survey data. The result suggested SRLUI might only benefit a subgroup of learners with passing grades. Thus, it is recommended that future research identify various subgroups of learner profiles in MOOC environments and to consider how to reach and support learners in different subgroups.
Notes: Department: Mathematics, Science, and Technology.

Thesis advisor: Yoo Kyung Chang.

Thesis advisor: Paulo Blikstein.

Thesis (Ed.D.)--Teachers College, Columbia University, 2021.