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Gaze-Driven Adaptive Learning with ChatGPT by Shin Maxwell Cabatuan is a document available to read on EtoBox.

What is Gaze-Driven Adaptive Learning with ChatGPT about?

This study presents a gaze-driven adaptive learning system that integrates real-time engagement prediction using gaze data with ChatGPT-generated summaries to enhance student engagement and learning outcomes. An experiment with 22 university students demonstrated that the system effectively predicts engagement levels and improves learning outcomes through adaptive interventions, particularly using a Transformers model with an average accuracy of 68.15%. The findings suggest strong correlations between gaze

Author
Shin Maxwell Cabatuan
Language
EN

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