Exploring the Adoption Phenomenon of Artificial Intelligence by Doctoral Students Within Doctoral Education

Abstract

The adoption of artificial intelligence (AI) in academia is an emerging field of interest. However, there is scant literature that explores the phenomenon of AI adoption by graduate students in doctoral education. This study employs collaborative autoethnography to explore and better understand the nuances of how doctoral students experience AI technologies within academic pursuits. A critical analysis of data revealed that the collective researcher-participant experiences offered the primary overarching theme of adoption strategy, with four distinct subthemes: adoption fear, adoption resistance, adoption feasibility, and adoption ethics. The findings suggest a balanced approach to AI adoption depends on the development of comprehensive strategies that are informed by a deep understanding of both the technological capabilities and the human factors involved. We urge both doctoral students and educators involved in doctoral programs to think critically about these identified themes. For doctoral students, this analysis offers valuable insights into challenges associated with integrating AI technologies into formal learning environments, potentially enhancing a management strategy for their doctoral studies. Educators tasked with integrating and evaluating AI technologies for doctoral coursework may develop a deeper understanding of the challenges their students may encounter during the adoption process.