Author ORCID Identifier
Dr. David Wolff ORCID ID is: https://orcid.org/0009-0009-2855-8472
Dr. Melissa Wolff ORICID ID is: https://orcid.org/0009-0004-8766-3866
Dr. Mark Diacopoulos ORCID ID is: https://orcid.org/0000-0002-1861-8787
Abstract
Higher Education faculty balance time in teaching, scholarship, and service, along with many other duties in their roles (Office of Occupational Statistics and Employment Projections, 2024). In our efforts to be stewards of our time and craft, faculty look for ways to be more efficient in these areas. With the increase of Artificial Intelligence (AI) in our personal and professional lives, this paper discusses the use of Generative Artificial Intelligence (GAI), Microsoft Copilot, as an analytic tool in the qualitative data analysis process. Qualitative data was collected from transcripts of recorded meetings and an online journal that included text and photograph entries. The qualitative data from these documents were uploaded to Copilot to analyze for codes and patterns using both inductive and deductive coding methods. The output is presented and discussed raising issues of accuracy, reliability, and dependability of Copilot’s output.
Recommended Citation
Wolff, D., Wolff, M., & Diacopoulos, M. (2026). Collaborating with our AI Research Companion: Exploring the Use of Microsoft Copilot to Conduct Inductive and Deductive Coding in Qualitative Research. The Interactive Journal of Global Leadership and Learning, 4(3). https://doi.org/10.55354/2692-3394.1083
Included in
Curriculum and Instruction Commons, Educational Leadership Commons, Educational Methods Commons, Educational Technology Commons, Higher Education and Teaching Commons, Leadership Studies Commons, Online and Distance Education Commons, Scholarship of Teaching and Learning Commons
