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A comparison of Human, GPT-3.5, and GPT-4 Performance in a University-Level Coding Course
March 26, 2024, 4:51 a.m. | Will Yeadon, Alex Peach, Craig P. Testrow
cs.CL updates on arXiv.org arxiv.org
Abstract: This study evaluates the performance of ChatGPT variants, GPT-3.5 and GPT-4, both with and without prompt engineering, against solely student work and a mixed category containing both student and GPT-4 contributions in university-level physics coding assignments using the Python language. Comparing 50 student submissions to 50 AI-generated submissions across different categories, and marked blindly by three independent markers, we amassed $n = 300$ data points. Students averaged 91.9% (SE:0.4), surpassing the highest performing AI submission …
abstract arxiv chatgpt coding comparison course cs.cl engineering gpt gpt-3 gpt-3.5 gpt-4 gpt-4 performance human language mixed performance physics prompt python python language study type university variants work
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