Latifah Hamdan Alghamdi, Talal Musaed Alghizzi
This exploratory cluster-randomized mixed-methods study examined reading development and learner experience across AI-adaptive, teacher-differentiated, and non-differentiated EFL reading instruction. Eighty-seven university-level EFL learners, classified by CEFR proficiency, completed a 12-week intervention across four intact classrooms: two AI-adaptive, one teacher-differentiated, and one non-differentiated. Reading development was assessed using equated parallel-form IELTS-format tests calibrated through Rasch modeling and CEFR cut-score mapping. Learner experience was assessed using multi-item measures with satisfactory internal consistency and preliminary evidence of structural validity for cognitive load, engagement, instructional comfort, and perceived ownership of reading achievement, supplemented by qualitative reflections. Because instructional condition was assigned at the classroom level and only four clusters were available, reading development patterns were interpreted primarily through descriptive comparison of the recoverable model-implied pre-to-post patterns, with participant-level mixed-design ANOVA and cluster-adjusted mixed-effects modeling reported as secondary analyses. The pooled AI-adaptive classrooms showed a larger model-implied pre-to-post increase than the comparison classrooms, while both secondary analyses showed the same directional pattern but substantial uncertainty. Descriptively, learners in the AI-adaptive classrooms reported lower cognitive load and higher engagement, instructional comfort, and perceived ownership of reading achievement. These findings provide preliminary classroom-based evidence of favorable patterns associated with AI-adaptive personalization but do not establish causal or generalizable instructional effects. Larger cluster-randomized studies are needed to separate instructional effects from classroom-level influences and examine proficiency-related differences.