Artificial Intelligence Applications for Students with Learning Disabilities: A Systematic Review

  • Iftikhar Bhatti
  • Syed Farooq Mohi-U-din
  • Yawar Hayat
  • Mehtab Tariq
Keywords: learning challenges, synthetic intelligence, developmental reading disability, number dyslexia, tailored education, technology integration model for learners with disabilities


This review study endeavors to elucidate the utilization of artificial intelligence (AI) in assisting students with learning disabilities (SWLDs). Among the 16 studies examined, dyslexia was the primary focus in 10 instances, with only one study concentrating on dyscalculia, and the remainder addressing learning disabilities in a broader context. Notably, only half of the studies targeted school-age children. Across these studies, seven distinct categories of AI applications were identified, encompassing adaptive learning, facial expression analysis, chatbots, communication aides, mastery learning systems, intelligent tutoring systems, and interactive robots. Among these, adaptive learning emerged as the most prevalent. Employing the SAMR-LD (Substitute, Augment, Modify, Redefine - Learning Disability) model, it was discerned that AI has been applied in diverse capacities to support SWLDs, with instances observed across substitution, augmentation, modification, and redefinition levels. While the findings underscore the potential of AI in aiding SWLDs, the limited number of empirical studies also highlights substantial gaps, indicating the necessity for further research into AI's broader role beyond mere identification and diagnosis of learning disabilities in this population.


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How to Cite
Bhatti, I., Mohi-U-din, S. F., Hayat, Y., & Tariq, M. (2024). Artificial Intelligence Applications for Students with Learning Disabilities: A Systematic Review. European Journal of Science, Innovation and Technology, 4(2), 40-56. Retrieved from