The Impact of AI‑Powered Adaptive Learning Tools on Differentiated Instruction In K‑12 Classrooms: A Case Study of ESL Learners in Pakistan

Abstract

With the proliferation of artificial intelligence (AI) in educational technology, AI‑powered adaptive learning tools have emerged as promising mechanisms for supporting differentiated instruction in diverse K‑12 classrooms. This study investigates their impact on English as a Second Language (ESL) learners in Pakistani schools, examining how AI‑enhanced personalization influences learning outcomes, engagement, and teacher efficacy. Grounded in Vygotskian and constructivist paradigms, we use a mixed-methods case-study approach, integrating quantitative pre-/post‑tests and qualitative teacher and student interviews across urban and rural schools. Findings reveal that AI adaptive tools significantly improved ESL proficiency, increased learner motivation, and aided teachers in customizing instruction. However, limitations such as technological access, teacher training, and cultural appropriateness emerged. The study concludes with recommendations for policy, practice, and future research, emphasizing the importance of infrastructure, capacity-building, and context‑sensitive design to harness AI's potential in differentiated learning.