Can Large Language Models Replace a Professor?

Abstract

As Large Language Models (LLMs) become increasingly integrated into educational and research environments, questions arise regarding their utility in mentoring undergraduate research and supporting classroom instruction. This paper outlines general guidelines for the effective use of LLMs in research and education, including a comparative analysis of various LLMs to evaluate their respective performance in planning interactive lessons. Findings suggest that LLMs can support lesson planning if seeded with ideas for learning objectives that come from additional background research and human ingenuity, iterate to find better interactive activities, and draw from multiple LLMs to avoid the typical weaknesses of a single LLM. In research mentoring, LLMs support efficient and high-quality output if one can engineer a suitable prompt, aided by background knowledge from some other source. The biggest barrier to LLM effectiveness is their confident hallucinations and lack of accuracy and creativity, but guidelines are provided here that should allow users to get beyond the pedestrian and sometimes incorrect output of the LLMs. LLMs should not replace human instruction and mentorship, but rather, should be seen as supplements that demand informed and reflective use. <em>Primary Image:</em>&nbsp;Can a professor be replaced with a Large Language Model? It could democratize education. We investigate the benefits and pitfalls of doing so.

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