Evaluating Academicians’ Perspectives on Education-based Assessments Strategies with Generative AI (GenAI)

  • Zhang Guangtian
  • Xiao Min
  • Zuraidah Abdullah
  • Kenny S.L Cheah


This study investigates the use of Generative AI (GenAI), in university assessments in Malaysia to understand its impact on evaluations. It explores the implications, challenges and academic viewpoints related to this advancement. The research methodology involves a combination of methods, including gathering feedback from education experts at three universities using a 5-point Likert scale. The main results show that educators generally see AI as beneficial for improving assessment accuracy but highlight some considerations that need attention. Additionally, the findings suggest that while AI can enhance assessments by providing optimized learning experiences ethical issues such as data privacy and excessive automation need to be addressed. Educators also acknowledge the importance of training programs to help them develop the skills needed to integrate AI into their practices effectively. The study concludes that although AI shows potential for transforming education, maintaining a balance between technology and human-centered learning is crucial for implementation.


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How to Cite
GUANGTIAN, Zhang et al. Evaluating Academicians’ Perspectives on Education-based Assessments Strategies with Generative AI (GenAI). Asian Journal of Research in Education and Social Sciences, [S.l.], v. 6, n. 2, p. 246-262, june 2024. Available at: <https://myjms.mohe.gov.my/index.php/ajress/article/view/26861>. Date accessed: 26 july 2024.
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