Adoption of Generative AI Tools In Higher Education: The Role of Attitude, Subjective Norms, and Perceived Behavioural Control
TL;DR
The proposed framework suggests that students who perceive AI tools as useful and beneficial are more likely to develop positive attitudes toward their use, and students who perceive AI tools as useful and beneficial are more likely to develop positive attitudes toward their use.
Abstract
Artificial Intelligence (AI) technologies are increasingly transforming higher education by providing innovative tools that support students in learning, academic writing, and information processing. Despite the rapid adoption of generative AI tools such as ChatGPT, Grammarly, and QuillBot, the factors influencing undergraduate students’ intention to use these tools for learning remain insufficiently understood. This study aims to examine the determinants of students’ intention to use AI tools based on the Theory of Planned Behaviour (TPB). Specifically, the study investigates the influence of attitude, subjective norms, and perceived behavioural control on students’ behavioural intention to adopt AI technologies in academic contexts. This study adopts a quantitative approach, where data will be collected from approximately 300 undergraduate students from Universiti Teknologi MARA (UiTM), Malaysia, using a structured questionnaire. The measurement items are adapted from established literature and assessed using a five-point Likert scale. The collected data will be analysed using Partial Least Squares Structural Equation Modelling (PLS-SEM) through SPSS and SmartPLS software. The proposed framework suggests that students who perceive AI tools as useful and beneficial are more likely to develop positive attitudes toward their use. In addition, social influences from lecturers, peers, and institutions are expected to shape students’ perceptions and acceptance of AI tools. Furthermore, students’ confidence in their digital skills and access to technological resources may enhance their perceived behavioural control, which in turn strengthens their intention to use AI tools. This study contributes to the growing body of knowledge on AI adoption in higher education by applying TPB in the context of generative AI tools. The findings are expected to provide practical insights for universities in developing policies, training programs, and ethical guidelines to promote responsible and effective use of AI in academic learning environments.