Affective Artificial Intelligence in E-Learning: Towards Emotion-Aware Educational Technologies for Mental Wellbeing and Inclusion

Abstract

Emotion-aware technologies are increasingly shaping the future of digital education. This study explores the potential of affective artificial intelligence (AI) to recognize and respond to learners' emotional states in online learning environments. While such systems promise more inclusive, supportive, and responsive digital classrooms, their design in addition raises important ethical and psychosocial concerns. Drawing from affective computing, digital empathy, and inclusive pedagogy, this conceptual study examines how AI can be used not only to monitor engagement however in addition to promote emotional wellbeing and learner autonomy, especially for students at risk of emotional distress, disconnection, or exclusion. Through analysis of existing technologies and case-informed reflections, the paper identifies both the opportunities and the limitations of affective systems in e-learning. A preliminary framework for ethically aligned emotional AI is proposed, emphasizing transparency, user agency, and safeguards against bias and manipulation. These insights aim to inform educators, designers, and policymakers working toward more humane, equitable, and emotionally intelligent uses of AI in lifelong learning.