A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilities

  • Iftikhar Bhatti
  • Mehtab Tariq
  • Yawar Hayat
  • Aftab Tariq
  • Saad Rasool
Keywords: Artificial Intelligence, multimodal sensor data, intellectual disabilities, adaptive learning system, machine learning


Educational tools using Artificial Intelligence (AIEd) have been implemented to provide automated learning support for typical students. This innovative field focuses on using data and machine learning to detect a student's emotional state, with the goal of shifting them from unproductive emotions to more positive, learning-enhancing ones like engagement. However, AIEd systems that include emotion recognition often overlook students with intellectual disabilities. Our system employs multimodal sensor data and machine learning to identify three key emotional states related to learning (engagement, frustration, boredom). It then adjusts the educational content to keep the student in an ideal emotional state, optimizing learning effectiveness. To evaluate this adaptive learning system, we conducted studies with 67 participants aged 6 to 18, who served as their own controls, in sessions that used the system. These sessions alternated between using the system for both emotional state detection and learning progress to choose content (intervention) and relying solely on learning progress (control) for content selection. Remarkably, a lack of boredom was most strongly linked to better learning outcomes, while both frustration and engagement also showed positive correlations with achievement. Sessions using the intervention showed significantly more engagement and less boredom compared to control sessions, although there was no significant difference in achievement. These results indicate that customizing activities based on the learner's emotional state can boost engagement and foster emotions that are beneficial for learning. Nevertheless, longer-term studies are needed to assess the impact on actual learning achievements.


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How to Cite
Bhatti, I., Tariq, M., Hayat, Y., Tariq, A., & Rasool, S. (2023). A Multimodal Affect Recognition Adaptive Learning System for Individuals with Intellectual Disabilities. European Journal of Science, Innovation and Technology, 3(6), 346-355. Retrieved from https://ejsit-journal.com/index.php/ejsit/article/view/343