Empowering ESL Learners: Implementation of AI and Adaptive Learning Technologies

Abstract

Rapid advancements in the field of Artificial Intelligence (AI) and adaptive learning have revolutionized the way educational processes occur, especially in ESL settings. This paper seeks to evaluate the impact of implementation of AI and adaptive learning on the engagement and learning of university-level ESL learners. For this purpose, quantitative approach was adopted; and 250 ESL learners were targeted through a survey based on the 5-point Likert scale. Four primary constructs were incorporated in the proposed conceptual framework namely AI Usage (AIU), Adaptive Learning (AL), Student Engagement (SE) and Learning Outcomes (LO). Data analysis was conducted by utilizing Partial Least Square Structural Equation Model (PLS-SEM). Results demonstrate that both AI usage and AL have significant positive influences on SE. In addition, AL has a comparatively greater influence as compared to AI due to the reason that AL is personalized learning. Besides, SE is found to have the greatest influence on LO, which confirms the role of student engagement as a mediator between technology usage and learning outcome. Also, AI usage has a positive influence on LO with a smaller magnitude as compared to SE.

Overall findings of this study highlight the significance of using AI-based technology and personalized learning systems to increase student engagement and improve their learning in the field of ESL. This study makes an important contribution to literature through employing PLS-SEM in ESL setting, which has been used quite rarely before. Practical implications have been discussed for educators, institutions and policymakers to enhance the process of ESL learning through use of technology. Future research could further investigate other factors like learner satisfaction, digital literacy etc.