ProCoT: Stimulating Critical Thinking and Writing of Students through Engagement with Large Language Models (LLMs)
Authors: Tosin Adewumi, Lama Alkhaled, Claudia Buck, Sergio Hernandez, Saga Brilioth, Mkpe Kekung, Yelvin Ragimov, Elisa Barney
Abstract: We introduce a novel writing method called Probing Chain of Thought (ProCoT), which prevents students from cheating using a Large Language Model (LLM), such as ChatGPT, while enhancing their active learning through such models. LLMs have disrupted education and many other feilds. For fear of students cheating, many educationists have resorted to banning their use, as their outputs can be human-like and hard to detect in some cases. These LLMs are also known for hallucinations (i.e. fake facts). We conduct studies with ProCoT in two different courses with a combined total of about 66 students. The students in each course were asked to prompt an LLM of their choice with one question from a set of four and required to affirm or refute statements in the LLM output by using peer reviewed references. The results show two things: (1) ProCoT stimulates creative/critical thinking and writing of students through engagement with LLMs when we compare the LLM solely output to ProCoT output and (2) ProCoT can prevent cheating because of clear limitations in existing LLMs when we compare students ProCoT output to LLM ProCoT output. We also discover that most students prefer to give answers in fewer words than LLMs, which are typically verbose. The average word counts for students, ChatGPT (v3.5) and Phind (v8) are 208, 391 and 383, respectively.
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