VTutor for High-Impact Tutoring at Scale: Managing Engagement and Real-Time Multi-Screen Monitoring with P2P Connections
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Abstract (arXiv)
Hybrid tutoring, where a human tutor supports multiple students in learning with educational technology, is an increasingly common application to deliver high-impact tutoring at scale. However, past hybrid tutoring applications are limited in guiding tutor attention to students that require support. Specifically, existing conferencing tools, commonly used in hybrid tutoring, do not allow tutors to monitor multiple students' screens while directly communicating and attending to multiple students simultaneously. To address this issue, this paper introduces VTutor, a web-based platform leveraging peer-to-peer screen sharing and virtual avatars to deliver real-time, context-aware tutoring feedback at scale. By integrating a multi-student monitoring dashboard with AI-powered avatar prompts, VTutor empowers a single educator or tutor to rapidly detect off-task or struggling students and intervene proactively, thus enhancing the benefits of one-on-one interactions in classroom contexts with several students. Drawing on insight from the learning sciences and past research on animated pedagogical agents, we demonstrate how stylized avatars can potentially sustain student engagement while accommodating varying infrastructure constraints. Finally, we address open questions on refining large-scale, AI-driven tutoring solutions for improved learner outcomes, and how VTutor could help interpret real-time learner interactions to support remote tutors at scale. The VTutor platform can be accessed at https://ls2025.vtutor.ai. The system demo video is at https://ls2025.vtutor.ai/video.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 12 May 2025.
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Citing papers per year: 2025: 1; 2026: 3.
4 papers.
- 2025AI tutoring can safely and effectively support students: An exploratory RCT in UK classroomscited by 3
- 2026When AI Agents Learn from Each Other: Insights from Emergent AI Agent Communities on OpenClaw for Human-AI Partnership in Educationcited by 1
- 2026LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedbackcited by 0
- 2026Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learningcited by 0
- 2026When AI Agents Learn from Each Other: Insights from Emergent AI Agent Communities on OpenClaw for Human-AI Partnership in Education17 Mar 2026
- 2026Chat-Based Support Alone May Not Be Enough: Comparing Conversational and Embedded LLM Feedback for Mathematical Proof Learning21 Feb 2026
- 2026LLM-based Multimodal Feedback Produces Equivalent Learning and Better Student Perceptions than Educator Feedback21 Jan 2026
- 2025AI tutoring can safely and effectively support students: An exploratory RCT in UK classrooms29 Dec 2025