Unveiling emotional reaction and satisfaction in e-learning with face tracking

This study explores the user experience (UX) of students on e-learning platforms, emphasizing emotional expression and satisfaction. It enhances existing research by applying usability tests and surveys to assess the emotional impact of online learning. The study’s novelty lies in its focus on emotional expression, which, along with cognitive issues and engagement, plays a vital role in shaping the quality of learning outcomes. It compares the effectiveness of a real-timeface and eye recognition method (MIORA) with a retrospective questionnaire (SAM) for measuring emotional responses.Results indicate that the real-time method is more accurate and reliable, capturing transient emotional states with machine learning. Unlike retrospective assessments, which are prone to memory biases, the real-time method provides immediate, objective data for dynamic understanding and instant feedback. These insights are crucial for improving e-learning platform design, enhancing user engagement, and enabling real-time adaptations, leading to more engaging and rewarding online learning environments.