The Impact of AI-Powered Personalized Learning on ESL Student Outcomes

Abstract

This study investigates the impact of AI-powered personalized learning on ESL student outcomes through a mixed-methods approach involving 120 university-level learners. Results demonstrate statistically significant improvements in language proficiency (p < .001), with notable gains in vocabulary retention (40%), grammar accuracy (25%), and pronunciation (35%) compared to traditional methods (Jarrah et al., 2023; Ganesh dandu & G. Mohanacharyulu, 2023). Qualitative data reveal enhanced student engagement through gamified AI tools and increased self-directed learning behaviors. However, challenges persist in algorithmic bias, data privacy, and equitable access (Wang et al., 2023; Li & Zhou, 2022). The findings align with UN Sustainable Development Goal 4 (SDG 4), advocating for AI as a tool to promote inclusive education while emphasizing the irreplaceable role of teachers in addressing cultural and emotional learning dimensions (Rustamova & Rakhmatullaeva, 2023). The study concludes with recommendations for ethical AI integration, hybrid pedagogical models, and targeted teacher training to optimize ESL outcomes globally.