Date
Publisher
arXiv
Transforming educational technologies through the integration of large language models (LLMs) and virtual reality (VR) offers the potential for immersive and interactive learning experiences. However, the effects of LLMs on user engagement and attention in educational environments remain open questions. In this study, we utilized a fully LLM-driven virtual learning environment, where peers and teachers were LLM-driven, to examine how students behaved in such settings. Specifically, we investigate how peer question-asking behaviors influenced student engagement, attention, cognitive load, and learning outcomes and found that, in conditions where LLM-driven peer learners asked questions, students exhibited more targeted visual scanpaths, with their attention directed toward the learning content, particularly in complex subjects. Our results suggest that peer questions did not introduce extraneous cognitive load directly, as the cognitive load is strongly correlated with increased attention to the learning material. Considering these findings, we provide design recommendations for optimizing VR learning spaces.
Study at a glance
- Question: How do questions asked by AI classmates in a virtual classroom affect student attention, engagement, and learning?
- Setting and data: Students in an AI-driven virtual reality classroom.
- Method: Compares student attention, engagement, and cognitive load across conditions in a virtual classroom.
Why it matters
Integrating large language models with virtual reality offers potential for immersive and interactive learning experiences. However, the effects of these models on user engagement and attention in educational environments remain open questions.
Key findings
- In an AI-driven virtual classroom, questions asked by AI peers directed students' visual attention toward the instructional content, especially during complex subjects.
- Questions from AI peers did not appear to directly add distracting mental effort for students.
- Students' mental effort was strongly linked to increased attention paid directly to the learning materials.
Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
