Introduction to Generative AI in Higher Education

The rapid emergence of generative artificial intelligence (GenAI) has significantly transformed the landscape of higher education. This innovative technology provides advanced tools capable of generating various forms of content, including text, images, and code.

Determinants of Adoption

This study explores the adoption of GenAI from the perspective of the Unified Theory of Acceptance and Use of Technology (UTAUT). Key determinants influencing this adoption involve performance expectancy, effort expectancy, social influence, and facilitating conditions. Additionally, extended constructs such as perceived risk, trust, and AI literacy are examined, revealing a multifaceted approach to understanding user acceptance.

Findings and Implications

Findings from the study indicate that students exhibit a higher tendency to embrace GenAI due to its perceived academic advantages, user-friendliness, and normalization among peers. Conversely, academic staff remain more cautious in their acceptance, influenced by concerns regarding academic integrity, reliability, and institutional policies. Notably, performance expectancy consistently emerges as the primary predictor of GenAI adoption. Furthermore, facilitating conditions and organizational support are identified as critical for sustaining usage, especially among educators.

The study emphasizes the necessity of institutional strategies, including the development of AI literacy, the establishment of clear policy frameworks, and the initiation of training programs to promote responsible AI integration. Authored by Prof. Dr. Koh Kee Lee, DBA, this research contributes valuable insights into the behavioral intentions and usage patterns of GenAI, ultimately aiming to enhance technology acceptance in academic settings.