Skip to content

Author

Fatin Nadhirah Zabani

1 paper indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

Review Open access 2026

Generative Artificial Intelligence in Higher Education: Adoption and Academic Integrity Perceptions among Malaysian Undergraduates

The increasing accessibility of generative artificial intelligence (GenAI) tools is transforming academic practices in higher education. This study investigates the adoption of generative AI among undergraduate students in Malaysia, with particular attention to usage patterns, perceived academic benefits, and perceptions of academic integrity. A quantitative survey was conducted with 166 respondents, and the data were analysed using descriptive statistics, analysis of variance (ANOVA), and independent t-tests. The findings indicate a high level of generative AI adoption, with 97.6% of students reporting using AI tools for academic purposes. ChatGPT and Canva emerged as the most frequently used tools. Respondents generally perceived generative AI as beneficial for completing academic tasks, understanding course content, solving study-related problems, and enhancing the quality of academic work. At the same time, concerns were reported about plagiarism, overreliance on AI, and the need to disclose AI-assisted work in academic submissions. Inferential results further suggest that, although selected demographic differences exist in the use of certain tools and in some usage-related perceptions, perceptions of academic integrity are broadly consistent across age, gender, and level of study. These findings underscore the growing role of generative AI in higher education and the need for institutional policies that promote ethical, transparent, and responsible use.

A. A. Sharip, U. M. A. Jalil, R. M. Saidi et al. · 0 citations