Self-regulation is a core concept to understand the metacognitive, motivational, and emotional aspects of learning. The outbreak of COVID-19 resulted in large numbers of courses being shifted online, thus providing a large-scale setting to collect new empirical evidence to shed light on the specific challenges that different learner subgroups struggle with in the authentic online learning environment and then to provide practical implications to improve the learning outcomes by promoting learners’ online self-regulation. Based on a survey of 64,949 participants enrolled at 39 universities in a metropolitan city of China during the pandemic, we developed the Undergraduate Online Self-regulated Learning Questionnaire (UOSL), tested the reliability and construct validity of the UOSL items, and then built regression models to estimate the associations between online self-regulation and mastery of eight skills across different subgroups in a diverse student body. Disadvantaged subgroups such as rural, first-generation college students reported significantly lower UOSL scores as well as lower skill mastery in online learning. After controlling self-regulation in the regression model, these gaps related to student demographics have shrunk substantially and some become statistically insignificant (e.g., the gender gap in online skill mastery). The findings highlight the critical role of the targeted interventions of self-regulation to promote equity and enhance quality in the online teaching design and learning support.

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Self-regulation is a core concept associated with the metacognitive, motivational, and emotional aspects of learning. The COVID-19 pandemic provides a large-scale setting to collect new empirical evidence to test this conceptual framework in an authentic online learning environment. By reference to 64,949 participants enrolled at 39 universities in China, the authors developed the Undergraduate Online Self-Regulated Learning Questionnaire and estimated the associations among self-regulation, motivation, emotion, and skill mastery with regard to online learning across different subgroups of a diverse student body. The results demonstrated that males, rural students, lower-division undergraduates, first-generation college students, SEAM majors, and students at elite universities reported significantly lower UOSL scores. After controlling for motivation and emotion, these gaps decreased substantially and become statistically nonsignificant. The findings highlight the critical role played by targeted interventions in the creation of a supportive online environment for disadvantaged subgroups.