Adopting Artificial Intelligence in Higher Education: Insights from the UTAUT Framework on Students Intentions
DOI:
https://doi.org/10.24191/abrij.v11i1.8641Keywords:
Artificial Intelligence, Higher Education, Technology Acceptance, UTAUT FrameworkAbstract
The integration of Artificial Intelligence (AI) into higher education is gaining momentum, offering innovative tools that can improve student engagement, support individualized learning, and enhance academic performance. While global statistics indicate that approximately 86% of students have used AI for academic purposes, its adoption among Malaysian undergraduates remains relatively limited. This is despite ongoing national efforts such as the Malaysia Digital Economy Blueprint (MyDIGITAL), which seeks to accelerate digital transformation across sectors including education. Understanding the drivers and barriers to AI adoption in higher education is crucial for developing effective strategies that can enhance teaching and learning experiences. This study investigates the factors influencing students’ intentions to adopt AI in higher education settings. Guided by the Unified Theory of Acceptance and Use of Technology (UTAUT), the research focuses on four core constructs: performance expectancy, effort expectancy, social influence, and facilitating conditions. The findings aim to offer insights that can support effective strategies for AI adoption in Malaysia’s higher education landscape, benefiting educators, policymakers, and technology developers. This study will employ a quantitative, cross-sectional survey to examine factors influencing undergraduate students’ intention to use artificial intelligence (AI) in Malaysian higher education. Data will be collected from a convenience sample of undergraduate students through an online questionnaire adapted from the UTAUT framework. A minimum of 137 participants will be targeted to ensure sufficient statistical power. The data will be analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM) with SmartPLS, which is suitable for exploratory research involving complex models. This research is expected to advance understanding of technology acceptance in higher education by identifying key factors influencing students’ intention to use AI, offering insights for educators and policymakers to support effective AI integration. Ultimately, the study seeks to contribute to the broader adoption of AI technologies that can transform the educational experience.
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Copyright (c) 2020 Noorizan Mohamad Mozie, Norfazlina Ghazali, Liatul Izian Ali Husin
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