The impact of AI-enhanced educational technologies on reading comprehension skills development in students with learning disabilities: Towards individualized future education - Nasser Almutairi, Hind; Faleh Al-Osail, Abdulaziz; A. Alshehri, Mohammed; Ahmed Elhossiny Mohammed, Mohammed; Nasser Ayed Al-Dosari, Mashael; Ali Nemt-allah, Mohamed; Abdellatif, Mohamed (Research Journal in Advanced Humanities, 2025)
This study aimed to examine the effectiveness of AI-enhanced educational technologies compared to conventional instruction methods in improving reading comprehension skills among middle school students with learning disabilities through a quasi-experimental design. Twenty middle school students with identified learning disabilities from the Riyadh region, Saudi Arabia, were randomly assigned to experimental (n=10) or control (n=10) groups. The experimental group participated in an eight-week individualized AI-enhanced reading program featuring adaptive learning algorithms, multi-modal content delivery, and real-time personalized feedback. In contrast, the control group received conventional instruction. A comprehensive 25-item Reading Comprehension Skills Test assessed five domains: literal comprehension, vocabulary in context, inferential comprehension, critical analysis, and application/evaluation. Statistical analysis employed non-parametric procedures, including Mann-Whitney U tests for between-group comparisons and Wilcoxon signed-rank tests for within-group changes. Results demonstrated significant improvements for the experimental group across all reading comprehension domains compared to controls, with the most pronounced effects in critical analysis (p=.004) and total reading comprehension (p=.002). Within-group analysis revealed significant pre-to-post improvements in all domains for the experimental group, with effect sizes indicating substantial gains. Follow-up assessments confirmed sustained improvements without regression, suggesting durable intervention effects. The AI-enhanced platform's personalized, adaptive features effectively addressed the multifaceted nature of reading difficulties in students with learning disabilities, providing evidence for integrating AI technologies in special education interventions to promote individualized learning and long-term academic success.