Supporting Self-Regulated Learning with Generative AI: A Case of Two Empirical Studies

Abstract

Self-regulated learning (SRL) plays an important role in academic success. However, many students struggle to effectively self-regulate their learning and they need support to improve their SRL as well as their learning outcomes. Research shows that SRL supports are generally effective but often do not benefit the students who need them the most. One reason is that the support is rarely personalized to their individual needs. With the advancement of technology and, more recently, the proliferation of generative AI-powered technologies (e.g., chatbots and large language models), there is a potential to better meet students’ needs, and at the same time, a greater call to examine ways to personalize SRL support using AI. In this workshop presentation, we introduce two work-in-progress empirical studies to explore the use of generative AI chatbots, specifically OpenAI’s ChatGPT, as a peer feedback tool and as a study tool to enhance SRL and learning performance in writing and reading, respectively, in the setting of higher education. Preliminary results of the empirical studies will be shared in the workshop. The presentation will contribute to the pressing discussion on opportunities and considerations in using generative AI tools to support SRL.