Bridging Engagement Analytics and Task Management for Quality Online Education: An SDG 4 Approach

This paper outlines an end-to-end, real-time, multi-modal system, EduVision Analyzer, that bridges student engagement analytics with automated task management, directly addressing UN Sustainable Development Goal 4 (Quality Education). The system accepts post-class video and audio, with computer vision to extract attention, activity, and emotion, and Natural Language Processing (NLP) to generate a summary and infer actionable tasks. The system novelty lies at the direct integration with task management systems, with automated synchronisation of inferred deadlines and assignment to Trello boards. Unlike previous studies, concerned with engagement monitoring, our strategy outlines a closed-loop solution that maps analytics to concrete, structured support for students, with the benefit of yielding both real-time student accountability and instructional insights. Our solution is thus positioned ahead of the standard, older e-learning analytic tools.