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ChatGPT-4 with Code Interpreter can be used to solve introductory college-level vector calculus and electromagnetism problems

Authors
Tanuj Kumar,
Mikhail A. Kats
Date
Publisher
arXiv
We evaluated ChatGPT 3.5, 4, and 4 with Code Interpreter on a set of college-level engineering-math and electromagnetism problems, such as those often given to sophomore electrical engineering majors. We selected a set of 13 problems, and had ChatGPT solve them multiple times, using a fresh instance (chat) each time. We found that ChatGPT-4 with Code Interpreter was able to satisfactorily solve most problems we tested most of the time -- a major improvement over the performance of ChatGPT-4 (or 3.5) without Code Interpreter. The performance of ChatGPT was observed to be somewhat stochastic, and we found that solving the same problem N times in new ChatGPT instances and taking the most-common answer was an effective strategy. Based on our findings and observations, we provide some recommendations for instructors and students of classes at this level.
Study at a glance
  • Question: How well can different versions of ChatGPT solve college-level engineering-math and electromagnetism problems?
  • Setting and data: 13 college-level engineering-math and electromagnetism problems typically given to sophomore electrical engineering majors.
  • Method: Tests and compares how multiple versions of ChatGPT solve problems across repeated trials.
Why it matters

Understanding how ChatGPT 3.5, 4, and 4 with Code Interpreter perform on college-level engineering-math and electromagnetism problems informs instructors and students working with sophomore electrical engineering coursework.

Key findings
  • On sophomore college-level engineering-math and electromagnetism problems, ChatGPT-4 with Code Interpreter satisfactorily solved most problems most of the time.
  • ChatGPT-4 with Code Interpreter showed a major performance improvement over ChatGPT-4 and 3.5 without the tool.
  • Because ChatGPT's performance was inconsistent, generating multiple attempts in new chats and selecting the most common answer was an effective strategy.

Summary drafted with AI from the paper’s abstract and may contain errors. See the full paper for details.

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