AttentiveLearn: Personalized Post-Lecture Support for Gaze-Aware Immersive Learning

TL;DR

AttentiveLearn is a system that uses eye-tracking in VR lectures to create personalized quizzes, aiming to enhance motivation and engagement in immersive learning environments through post-lecture support.

Contribution

This paper introduces AttentiveLearn, a novel ecosystem that generates personalized quizzes based on attention data, addressing the gap in post-lecture support for immersive VR learning.

Findings

Improved reported motivation and engagement among learners.

Anecdotal evidence of increased attention over time.

No conclusive evidence of learning gains.

Abstract

Immersive learning environments such as virtual classrooms in Virtual Reality (VR) offer learners unique learning experiences, yet providing effective learner support remains a challenge. While prior HCI research has explored in-lecture support for immersive learning, little research has been conducted to provide post-lecture support, despite being critical for sustained motivation, engagement, and learning outcomes. To address this, we present AttentiveLearn, a learning ecosystem that generates personalized quizzes on a mobile learning assistant based on learners' attention distribution inferred using eye-tracking in VR lectures. We evaluated the system in a four-week field study with 36 university students attending lectures on Bayesian data analysis. AttentiveLearn improved learners' reported motivation and engagement, without conclusive evidence of learning gains. Meanwhile, anecdotal evidence suggested improvements in attention for certain participants over time. Based on our findings of the field study, we provide empirical insights and design implications for personalized post-lecture support for immersive learning systems.