As online learning becomes increasingly central to education, maintaining student engagement and fostering growth remain fundamental challenges. Advances in AI and deep learning now allow for the detection and analysis of learner engagement in real time, using camera-based emotion recognition and adaptive models. By providing a non-invasive, responsive framework, these technologies can enhance attention, motivation, and cognitive skill development, creating more personalized and effective digital learning experiences. Deep Learning for Engagement and Cognitive Growth in E-Learning critically explores the integration of deep learning and AI to detect, analyze, and enhance student engagement in digital learning platforms. Leveraging camera-based emotion recognition systems and real-time engagement models, the book presents a novel framework that supports cognitive skill development in e-learning without relying on physiological signals. Covering topics such as camera-based deep learning, deepfake detection, and personalized learning pathways, this book is an excellent academic resource for graduate and doctoral students, academicians and policymakers in higher education, administrators, researchers, and more.
