Camera-Based Deep Learning Framework for Real-Time Emotion-Aware Engagement Detection in E-Learning

<jats:p>The explosive expansion of digital learning platforms has revolutionized the manner in which students access, consume, and interact with academic content. Sustaining high levels of engagement within online spaces, though, remains perhaps the most critical challenge facing higher education. Conventional methods of measuring engagement—e.g., tracking presence, post-session questionnaires, or physiological sensors—are intrusively burdensome, not very reliable, and less than ideal for widespread implementation. Technological developments in artificial intelligence (AI) and deep learning provide non-invasive means, notably via camera-based emotion detection systems that are able to track and decipher learner engagement real-time. This chapter suggests a human-focused deep learning approach that incorporates facial emotion detection with adaptive learning routes to boost learner engagement and mental growth in e-learning contexts.</jats:p>