VTutor for High-Impact Tutoring at Scale: Managing Engagement and Real-Time Multi-Screen Monitoring with P2P Connections

2025-05-12

AI Summary

Existing hybrid tutoring tools inadequately support teachers in synchronously monitoring multiple student screens and delivering real-time, context-aware, personalized interventions. To address this, we propose VTutor—the first web-based remote tutoring platform integrating peer-to-peer (P2P) multi-screen monitoring with AI-driven virtual agent prompting. Built on WebRTC for low-latency screen sharing, VTutor incorporates a lightweight virtual agent engine, a real-time behavioral state recognition module, a multi-view monitoring dashboard, and a learning-science-informed prompting strategy framework. Empirical evaluation demonstrates that VTutor significantly improves teachers’ detection speed for disengaged or struggling students and enhances intervention timeliness. It maintains stable interactivity even under bandwidth-constrained conditions and effectively boosts responsiveness and personalization in large-scale hybrid one-to-one tutoring scenarios.

Technology Category

• Computer Vision: Multi-modal Vision
• Humans and AI: Game Design — Virtual Humans, NPCs and Autonomous Characters
• Intelligent Robots: Multimodal Perception & Sensor Fusion

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Virtualization and resource management in Web systems and infrastructures
• Economics, Online Markets and Human Computation: Sustainability of Web economics

Abstract

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.

Problem

• Guiding tutor attention to students needing support in hybrid tutoring
• Monitoring multiple students' screens simultaneously during tutoring sessions
• Sustaining student engagement with AI-powered avatars in large-scale tutoring

Innovation

• Web-based platform with P2P screen sharing
• AI-powered avatars for real-time feedback
• Multi-student dashboard for proactive intervention