Designing a recommender system to promote self-regulated learning in online contexts: A design-based study

Abstract

Self-regulated learning (SRL) is a prerequisite for successful learning. However, studies have reported that many students struggle with self-regulation in online learning, indicating the need to provide students with additional support for SRL. This study adopted a design-based research methodology to iteratively design, implement, and evaluate different SRL recommendation designs. The main study consisted of three cycles, which were conducted in a fully online graduate course. Eighty-one students who enrolled in this course over three semesters participated in the study. The qualitative results generated from student interviews were assessed immediately after each cycle, and students’ perceptions were adopted to refine the design of next cycle. The quantitative results were analyzed after the last cycle of the study to examine the effects of different SRL recommendation designs on students’ SRL skills and learning performance. The results showed that the different recommendations designs had significant effects on students’ SRL skills. The refined system adopted in the last cycle showed the greatest potential for promoting students’ SRL skills, although no significant effect was found on their learning performance. These findings resulted in a set of design guidelines that can shed light on future literature, including: (a) incorporate personalization into the design rationale, (b) ensuring the ease of use of the system, (c) enriching users’ learning experience, and (d) sustaining users’ motivation.