Enhancing Cognitive Reading Strategy Use for L2 Learners with Lower Working Memory through AI-Based Scaffolding

Abstract

This study investigates the impact of AI-based scaffolding tools on reading comprehension and cognitive strategy use among second language (L2) learners with lower working memory capacity. Specifically, it compares the effectiveness of adaptive, visual, and interactive scaffolding in enhancing reading proficiency and fostering strategic reading behaviors. Participants were randomly assigned to one of three scaffolding conditions or a control group. Pre- and post-intervention assessments measured changes in reading comprehension scores and self-reported strategy use via the Survey of Reading Strategies (SORS). Results indicated that learners in the adaptive scaffolding condition demonstrated significant improvements in both reading comprehension and the adoption of higher-order strategies such as predicting and summarizing. Qualitative feedback highlighted increased confidence and reduced cognitive load. These findings suggest that AI-based adaptive scaffolding can effectively support L2 learners with lower working memory by providing personalized, just-in-time assistance, thereby promoting deeper engagement with texts and more autonomous learning habits. Theoretical implications for cognitive load theory and practical applications for technology-enhanced language instruction are discussed.