Using Generative AI to Support Students' Self-Regulated Learning Skills

Overview

Self-regulated learning (SRL) is a process in which students actively plan, monitor, reflect, and adjust their learning progress to achieve their goals. Students with strong SRL skills generally perform better, making it essential to train them in SRL for enhanced learning performance. Recognising the importance of SRL, educators have experimented with various strategies to boost students' self-regulation skills. One such strategy involves having students complete a weekly planning exercise, outlining their learning goals for the week, time spent on the previous week's course activities, and knowledge gained during that time. However, a major drawback of these strategies is the absence of timely and personalised feedback from teachers. In this seminar, the speaker will showcase the key features of an innovative, generative AI-based chatbot system designed to support students' SRL during their learning activities.　

The deliverables of this research project include three working prototype chatbots to facilitate students' goal setting and planning, students' self-evaluation, and students' help-seeking. These three activities are some of the key processes in self-regulated learning. Other deliverables include publications concerning the design guidelines of using chatbots in education setting, and the effects of the chatbots upon students' SRL skills, perceived usefulness and ease of use.