Effective Generative AI Implementation in Developing Country Universities Academic Article in Scopus uri icon

abstract

  • This paper explores the integration of Generative Artificial Intelligence (Gen AI) into the teaching-learning-assessment processes within Higher Education Institutions (HEIs), particularly those located in developing countries. Through a mixed-methods approach, utilizing both qualitative insights from ChatGPT 4.0-generated 'Personas' representing international experts and quantitative analysis, this study evaluates the potential risks and delineates strategic pathways for the responsible implementation of Gen AI under limited financial and technological resources. The 'Personas' provided evaluations on a Likert scale, assessing risks, required actions, and resources necessary for Gen AI integration, which were then analyzed through descriptive statistics and visualized for interpretation. The findings highlight the most significant challenges as legal and ethical issues, technological dependence, and student development, echoing concerns noted in existing literature. To mitigate these risks, the study suggests a series of sequential strategies including promoting balanced technology use, investing in mental health initiatives, developing skills for educators, supporting AI literacy, creating culturally responsive AI content, and developing inclusive technology policies. Moreover, creating AI tools to enhance teaching and investing in equitable technological infrastructure are identified as resource-intensive actions, with a special emphasis on the prioritization of human resource investment as a starting point for HEIs with financial constraints. It is crucial to note the limitations of this work, given that the expert 'Personas' are bound by the training data and capabilities of the Large Language Model used. Therefore, the careful evaluation of the advice provided to ensure alignment with each institution's mission and philosophy is mandatory. Despite these limitations, the study offers valuable insights and a call-to-action for HEIs to lead the charge in integrating Gen AI across society. © 2024 IEEE.

publication date

  • January 1, 2024