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The World Economic Forum (World Economic Forum 2020) projects that, by 2025, the reorganisation of labour between humans and machines could result in the displacement of 85 million jobs while also creating 97 million jobs that are better suited to the new division of labour involving machines and algorithms. The aim of this small-scale study was to provide a basic understanding of one of the latest technological advancements, the Generative Artificial Intelligence (GAI) chatbot (Taecharungroj 2023), and how it is influencing teaching and learning in higher education. A particular focus was given to understanding the effectiveness of this technology, its adoption process, and challenges or limitations that arose, all from the perspectives of academics and policy-makers. Utilising a pragmatic stance towards grounded theory, this study employed an inductive and abductive approach towards understanding the real-world problem, generating actionable insights as theory. Rubin and Rubin’s (2012) responsive interviewing method was chosen for the primary source of data collection, utilising convenience and purposive sampling to identify information-rich sources. Data was analysed through a constant comparative process and qualitative coding techniques within MAXQDA software. The emergent prepositions highlight the necessity of revising assessment methods and academic policies in higher education to maintain a strong academic integrity. They go as far as to recommend the integration of multi-faceted evaluations, the adjustment of plagiarism policies, and fostering a culture of continuous pedagogical improvement to ensure a balanced and effective approach towards the utilisation of AI tools in higher educational settings.
David Deguara (Fri,) studied this question.