Boosting Reading Comprehension Through AI-Based Learning Tools
Keywords:
adaptive learning; educational technology; literacy instruction; intelligent tutoring systems; biometric feedbackAbstract
This study explores the effectiveness of Artificial Intelligence (AI)-based tools in enhancing reading comprehension among learners with varying proficiency levels. Utilizing a mixed-methods approach, the research combined quantitative pre- and post-tests with qualitative interviews and learner feedback. Students in the experimental group, who used adaptive AI-supported platforms, showed significantly greater improvements in comprehension scores compared to a control group. The most notable gains were observed among students with lower initial reading proficiency. High-performing learners, however, exhibited slightly reduced progress when relying extensively on AI-generated summaries, indicating potential drawbacks for advanced readers. The integration of biometric-enhanced AI tools further supported emotional readiness and reduced cognitive load. Qualitative data revealed increased motivation and engagement, with students describing the AI experience as interactive and personalized. Despite these benefits, however, concerns were raised about over-reliance on AI, particularly its impact on deep comprehension and critical thinking. The study concludes that AI-based reading tools can effectively support comprehension development, especially for struggling readers, but recommends their integration within a blended learning framework that includes teacher facilitation, ethical guidelines, and strategies for fostering active, critical engagement with texts.
https://doi.org/10.26803/ijlter.24.9.4
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