Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling

This study examines the impact and mediating mechanisms of AI-powered adaptive learning platforms on enhancing English reading proficiency. Using structural equation modeling (SEM) on data collected from 118 undergraduate students, this study validates a chained mediation model in which learner engagement mediates the relationship between satisfaction with platform functionalities and perceived learning outcomes. The results show that: (1) satisfaction with key functionalities, such as dynamic content adaptation and real-time feedback, significantly enhances learner engagement; (2) learner engagement strongly predicts perceived improvements in reading skills; and (3) the platform facilitates reading comprehension through a dual intervention mechanism integrating bottom-up decoding and top-down schema activation strategies. These findings address an empirical gap in the application of AI for receptive language development and provide theoretical, methodological, and practical implications for the design of intelligent educational systems and foster pedagogical innovation.