Artificial Intelligence as a Motivational Tool in English as a Second Language Learning: A Self-Determination Theory Perspective

Abstract

This study investigates the role of AI-driven tools as predictors of students’ academic performance at the university level. The objectives of the study were: (1) to analyze the level of AI tools usage among university students; (2) to determine the relationship between AI tools usage and academic performance; and (3) to explore gender differences in AI tools usage and academic performance, including its sub-dimensions. The population of the study comprised 119 graduate students from the Departments of English (n = 35), Computer Science (n = 25), and Education (n = 59). A census sampling technique was employed. The study adopted a descriptive, quantitative research design, and data were collected using a survey method. Two questionnaires were developed for data collection: one measuring AI tools usage consisting of 20 items, and the other measuring academic performance comprising three dimensions time management (8 items), class participation (7 items), and communication skills (5 items). Both instruments were based on a five-point Likert scale. Content validity was ensured through expert review, and reliability was established using Cronbach’s alpha. Data were collected through personal visits after obtaining formal approval from the university authorities. Descriptive statistics (mean scores) were used to analyze AI tools usage, while regression analysis was employed to examine the relationship between AI tools usage and academic performance. An independent samples t-test was used to explore gender differences in AI tools usage and academic performance, including its sub-dimensions. The results revealed a statistically significant and positive relationship between AI tools usage and academic performance. Female students constituted a larger proportion of AI tool users than male students. The study recommends that each academic department develop a structured plan for the effective integration of AI tools into teaching and learning. Although AI has strong potential to enhance student outcomes, ethical considerations and appropriate human oversight remain essential for its effective and equitable implementation in higher education.