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July 20, 2026The Interactive Journal of Global Leadership and Learning0 citations

Collaborating with our AI Research Companion: Exploring the Use of Microsoft Copilot to Conduct Inductive and Deductive Coding in Qualitative Research

DWDavid WolffMWMelissa WolffMDMark Diacopoulos

Key Points

  • This research examines how Microsoft Copilot can facilitate qualitative data analysis through coding methods.
  • Qualitative data collected from transcripts of recorded meetings and an online journal with text and photo entries.
  • Data was uploaded to Microsoft Copilot for analysis using inductive and deductive coding methods.
  • Copilot provided outputs highlighting different codes and patterns in the qualitative data.
  • Discussion on the accuracy, reliability, and dependability of Copilot's results was conducted.

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.

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Cite This Study

Wolff et al. (2026) studied this question.

synapsesocial.com/papers/6a5dba3f8bd453d3397ab785https://doi.org/10.55354/2692-3394.1083
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