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.

翻译：虚拟现实（VR）等沉浸式学习环境（如虚拟教室）为学习者提供了独特的学习体验，然而如何提供有效的学习者支持仍是一个挑战。尽管先前的人机交互研究已探索了沉浸式学习的课中支持，但课后支持方面的研究却很少，而课后支持对于维持学习动机、参与度和学习成果至关重要。为此，我们提出了AttentiveLearn——一个基于VR讲座中眼动追踪推断的注意力分布，在移动学习助手上生成个性化测验的学习生态系统。我们通过一项为期四周的实地研究对该系统进行了评估，共有36名大学生参与了贝叶斯数据分析课程的学习。AttentiveLearn提高了学习者自我报告的学习动机和参与度，但在学习成效方面未获得确凿证据。同时，个案证据表明部分参与者的注意力随时间推移有所改善。基于实地研究的结果，我们为沉浸式学习系统的个性化课后支持提供了实证见解与设计启示。