Paper Title
An Ai-Driven Virtual Study Room Integrating Attention Tracking, Emotion Recognition and Adaptive Learning

Abstract
The rapid expansion of remote and hybrid education has created a demand for intelligent virtual learning environments that can sustain learner attention, support collaboration, and provide adaptive academic assistance. Most existing online learning platforms emphasize communication and content delivery while offering limited insight into learners’ cognitive and emotional states, leading to reduced engagement and ineffective collaboration during extended virtual sessions.This paper presents an AI-driven Virtual Study Room as a real-time collaborative learning framework integrating multi-modal artificial intelligence with synchronous communication technologies. The proposed system combines WebRTC based audio–video interaction, computer-vision-based attention and emotion recognition, machine-learning-driven adaptive focus scheduling, and transformer-based natural language processing for real-time summarization and academic support. Unlike review-based or prototype-level studies, this work introduces a complete working model methodology detailing system architecture, data pipelines, real-time inference, and analytics-driven feedback.The framework is designed for scalable and ethical deployment in multi-user environments and dynamically adapts to learners’ engagement patterns, improving focus retention, collaborative efficiency, and overall learning outcomes. Keywords - Virtual Learning Environment, Artificial Intelligence in Education, Attention Tracking, Emotion Recognition, Adaptive Focus Timer, Natural Language Processing.