Factors influencing artificial intelligence (AI) adoption among Malaysian students: A partial least square-structural equation modeling approach
DOI:
https://doi.org/10.24200/jonus.vol10iss2pp475-493Abstract
Background and Purpose: Artificial Intelligence (AI) is transforming higher education by enhancing learning experiences through personalised instruction, automated assessments, and intelligent tutoring systems. In Malaysia, AI adoption among students is gaining momentum, and it is influenced by digital literacy, perceived usefulness, and social influence. This study examines the key factors influencing AI adoption among Malaysian students.
Methodology: A survey research design was employed, utilising a structured questionnaire distributed to 286 students across four Malaysian universities. 224 valid responses were analysed using Partial Least Square (PLS-SEM) to test the hypothesised relationships among the variables.
Findings: Results indicate that social influence has the most substantial effect on AI adoption (β = 0.503, p < 0.001), followed by perceived usefulness (β = 0.236, p < 0.001) and digital literacy (β = 0.188, p = 0.036). These findings suggest that students are more likely to adopt AI when they observe peers and educators using it effectively. Additionally, students who perceive AI as beneficial for academic performance are more willing to engage with AI technologies.
Implication: The study contributes to understanding AI adoption in higher education; institutions can better prepare students for an AI-driven academic and professional landscape by addressing the identified factors.
Keywords: AI adoption, digital literacy, Malaysian students, perceived usefulness, social influence.
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