Do LLMs write like experts? The distinctive style of large language models and their role in student learning
Tuesday, Aug 5: 9:35 AM - 9:55 AM
Topic-Contributed Paper Session
Music City Center
Statistical writing is a key part of the undergraduate statistics curriculum, as it both helps students learn to reason about complex ideas and teaches them an important professional skill. As large language models (LLMs) offer increasingly sophisticated tools for automating writing, we must ask what effect they have on
the development of students as statisticians and statistical writers. We describe the results of several experiments comparing the grammatical and rhetorical style of students, experts, and LLMs, showing significant differences in how LLMs manage information, express confidence, and structure sentences. The
results suggest that LLMs do not effectively adapt their style to the genre and audience of their writing, and we explore the implications this has for teaching. If students offload the work of writing to a tool that does not write like a data scientist, how can we teach them to communicate like an expert data scientist?
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