EXPLORING THE RELATIONSHIP BETWEEN AI USAGE, SELF-EFFICACY, AND ACADEMIC MOTIVATION AMONG ENGLISH LANGUAGE LEARNERS
DOI:
https://doi.org/10.63878/qrjs442Abstract
This study explores the relationship between artificial intelligence (AI) usage, self-efficacy, and academic motivation among English language learners (ELLs). Thus, problems regarding low confidence, lack of motivation, and availability of quality resources in learning English become common nowadays due to the growing number of English language learners globally. The adoption of AI technologies like chatbots, adaptive platforms, and writing assistants has emerged as increasingly creative solutions to the mentioned barriers by providing a direct, personalized, interactive, and scalable aid. These relationships were investigated from an experimental constructed within a quantitative/correlational/cross sectional research design. The sample of 200 English language learners taking courses from Lahore, Pakistan, was chosen because they have already used AI-driven tools for learning a language. It was measured using the following scales: self-created AI Usage Scale, the General Self-Efficacy Scale, and the Academic Motivation Scale. In addition, all the scales were highly reliable and based on a 5-point Likert scale. The results confirmed that AI usage had a positive relationship with the self-efficacy and academic motivation of learners. Furthermore, mediation analysis allowed to indicate self-efficacy as one of the most significant factors to clarify the influence of using AI on motivation. Thus, in the interactions between the learners and AI applications, they gain more confidence in their performance, which will lead to desire for them to learn a language further. These findings add to the evidence for the importance of the careful incorporation of AI into language learning. Using the capabilities of AI, teachers and policy makers can create personalized, interactive, and inclusive systems for learning, particularly in a limited resource and large school context. This solution can further improve learners' performance and reshape the future of teaching English language.
