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Superficially Plausible Outputs from a Black Box: Problematising GenAI Tools for Analysing Qualitative SoTL Data

By Mirjam Sophia Glessmer and Rachel Forsyth

We spent the last months reading, coding, discussing, re-coding, discussing some more, re-coding, discussing even more, and then consensus coding free-text answers of 449 students, completing the analysis, and submitting the manuscript. “Just for fun, let’s plug it all into ChatGPT!” Rachel said, and so we did. After a few seconds, out came an analysis that looked almost identical to what we had painstakingly and carefully done over weeks and weeks and weeks. “Wow!” “But I am kind of curious where the differences come from. What did it see that we didn’t?” Mirjam asked, and that is how it all began.

In the article “Superficially plausible outputs from a Black Box: problematising GenAI tools for analysing qualitative SoTL data,” we reported on what happened next. How we discovered, little by little, the problems with what we had thought was such a time saver. How, when we repeated the same prompt on the same data, the responses differed. How, when summarizing an interview, sometimes assumptions about the gender of speakers were made even though there was no indication at all in the text. How sometimes context was invented to expand on our data. Most problematically, how we cannot describe what was happening inside a Generative AI tool, and therefore it cannot fulfill a basic requirement of a scientific analysis: That you can describe a method and reproduce results.

For us as academic developers, this answers a question that we are asked over and over again by teachers: Can I use GenAI on student responses to save time? The answer is yes, of course you can, but you really should not. The answers you will get are not scientifically sound; they are a black box’s best guess of what would be said in the context. Also, you are not giving those student responses the attention and respect they deserve, nor demonstrating that you want to build a trusting relationship conducive to learning.

Read the TLI article here.

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