Artificial Intelligence Adaptation in Higher Education: Supervisors Efficacy in Detecting AI-Generated Research in Postgraduate Research

The growing integration of Artificial Intelligence (AI) in academic research presents both transformative opportunities and tough challenges, particularly regarding the originality and authenticity of postgraduate students’ research as well as heightened concerns among supervisors regarding their ability to distinguish between human-generated and AI-generated research. The study examined postgraduate supervisors’ knowledge of AI tools, their detection capabilities, and the level of institutional preparedness in detecting AI-generated research. Using a quantitative approach, data from 34 respondents was analyzed to uncover the complexities of managing AI-generated material in research contexts. The findings revealed that most supervisors were aware of AI tools; their familiarity was largely limited to ChatGPT, with little knowledge of other advanced tools such as Jasper.ai and Perplexity AI. Supervisors reported significant difficulties in detecting AI-generated content and relied heavily on manual reviews and Turnitin. Furthermore, institutional policies were perceived as inadequate with critical gaps in training, enforcement mechanisms, and adaptability to evolving AI technologies. A striking disconnect existed between supervisors’ knowledge of AI tools and their detection capabilities, underscoring an urgent need for comprehensive regular and continuous training, promoting inter-institutional collaboration, and proactive policies to safeguard research integrity in an AI-driven academic landscape. The recommendations aim to empower supervisors with the expertise and resources necessary to navigate the ethical complexities of AI in postgraduate research.