Guiding Graduate Students to Integrate Artificial Intelligence into Qualitative Research Methods: Considerations for Cautious Optimism

• In Event: Too much of a good thing? How AI is (re)shaping academic careers in higher education

Abstract

Artificial intelligence (AI) has transformed traditional approaches to qualitative analysis, enabling rapid identification of themes, making the qualitative coding process more expedient for researchers working alone and graduate students learning the trade. However, with new technology, there are threats to validity. Thus, we argue that researchers, and in particular those training the next generation of qualitative researchers, should be cautiously optimistic about integrating AI into qualitative research methods. To test this assertion, we compare results from two sets of analysis: one done by a team of three researchers, and one by AI. Results show that while AI can be introduced to graduate students as a tool in their qualitative inquiry, it should not (yet) replace human interpretation of qualitative data.

Authors

• Joanna R. Smith, University of Auckland

• Heather McClure, Center for Equity Promotion

• Angtola Huy, University of Auckland

• Rita Svanks, University of Oregon

• Claudia Vincent, University of Oregon