Abstract: The rapid transformation of education into digital platforms has emphasized the need to improve virtual learning experiences by understanding students' emotions during lectures. Emotional states directly impact students’ focus, engagement, and learning outcomes, making real-time emotion analysis a valuable tool for enhancing teaching methodologies. This research presents an advanced emotion-based interactive dashboard designed to analyse students' facial expressions during online lectures, offering actionable insights to educators for improving teaching strategies and engagement. A key challenge in emotion recognition is dealing with occluded facial data caused by factors such as poor lighting, low resolution video, or face coverings. To address this, we employ a regenerative Generative Adversarial Network (GAN) capable of reconstructing occluded regions of the face while preserving critical emotional cues. The reconstructed data is processed using a deep learning model that predicts and classifies emotions into categories such as happiness, sadness, anger, surprise, fear, and neutrality. These emotional insights are then integrated into an intuitive dashboard that combines contextual data, such as the subject being taught, teaching faculty, and session-specific parameters. The dashboard offers dynamic visualization of emotion distribution, engagement trends, and real-time analytics, enabling educators to identify patterns in student behaviour. The system was validated using the CK+ dataset, achieving notable accuracy in classifying various emotions, even under conditions of partial facial occlusion. The integration of emotion-based analytics provides a unique approach to monitoring class engagement, identifying struggling students, and fostering personalized learning experiences. By combining advanced deep learning techniques with real-time analytics, the proposed system has the potential to redefine the future of online education, making it more responsive, adaptive, and student centered.
Keywords: Analytical Dashboard, Regenerative Generative Adversarial Network (GAN), Occluded facial data, Real time emotion.
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DOI:
10.17148/IJARCCE.2025.14676
