The Usage of AI in Academics: Its Impact on Learning Autonomy and Academic Motivation among University Students

Abstract

Artificial Intelligence (AI) has become an important component of higher education, offering personalized learning experiences and enhancing students' engagement in the learning process. The present study aimed to examine how AI can contribute to the field of education by understanding the impact it has on learning autonomy and academic motivation among university students. A quantitative correlational cross sectional research design was used. The sample was 226 university students from various universities selected using convenient sampling technique. Three questionnaires were used to collect data: the Questionnaire on the Use of AI in Education (QUIA; Vera, 2023), RATTC Self-Directed Learning Scale (Lounsbury & Gibson, 2009), and Academic Motivation Scale (AMS; Vallerand et al., 1992). Data were analyzed statistically using SPSS, descriptive statistics, reliability analysis, Pearson correlation and regression analysis. The results showed strong positive connections between the use of AI in learning, the autonomy of learning, and the motivation to learn. In addition, the use of AI was a significant predictor of learning autonomy and academic motivation. The findings indicate that students in universities who use AI technologies more are more motivated in learning and self-directed learning. The results underscore the potential of AI-driven learning tools to foster self-directed learning and motivate students in higher education.