(AI)nterventions: Exploring the effects of Gen-AI Support and prompting on Self-Regulated Learning

Abstract

In facilitating effective learning processes, self-regulated learning (SRL) is a widely acknowledged concept in the educational field. When applying learning from texts, learners are expected to self- regulate by employing various learning strategies, such as summarization. However, summarization can be challenging for learners who are not skilled nor trained. The availability of Gen-AI could potentially contribute to the design of innovative interventions supporting learners’ SRL when learning from texts by summarizing complex texts to aid text comprehension. This study aims to gain insights into the effects of Gen-AI supported interventions on self-regulated learning (especially metacomprehension accuracy) and perceived cognitive load. Participants (N = 105) were randomly assigned to four conditions: 1) self-summary only, 2) self-summary with prompts, 3) Gen-AI summary only, 4) Gen-AI summary with prompts. No significant effects were found for conditions on perceived cognitive load or metacomprehension accuracy. By incorporating both SRL and cognitive load theory, this study sets the stage for the design of future Gen-AI interventions to promote SRL.