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ChatGPT & Mechanical Engineering: Examining performance on the FE Mechanical Engineering and Undergraduate Exams

arXiv 2309.15866 ↗First posted 26 Sep 2023cs.CY cs.AIcited by 0

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Abstract (arXiv)

The launch of ChatGPT at the end of 2022 generated large interest into possible applications of artificial intelligence in STEM education and among STEM professions. As a result many questions surrounding the capabilities of generative AI tools inside and outside of the classroom have been raised and are starting to be explored. This study examines the capabilities of ChatGPT within the discipline of mechanical engineering. It aims to examine use cases and pitfalls of such a technology in the classroom and professional settings. ChatGPT was presented with a set of questions from junior and senior level mechanical engineering exams provided at a large private university, as well as a set of practice questions for the Fundamentals of Engineering Exam (FE) in Mechanical Engineering. The responses of two ChatGPT models, one free to use and one paid subscription, were analyzed. The paper found that the subscription model (GPT-4) greatly outperformed the free version (GPT-3.5), achieving 76% correct vs 51% correct, but the limitation of text only input on both models makes neither likely to pass the FE exam. The results confirm findings in the literature with regards to types of errors and pitfalls made by ChatGPT. It was found that due to its inconsistency and a tendency to confidently produce incorrect answers the tool is best suited for users with expert knowledge.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 44 references that are in the map. First posted on arXiv 26 Sep 2023.

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16 of 44 references.

References · 16

  1. 2023How is ChatGPT's behavior changing over time?cited by 270
  2. 2023Mathematical Capabilities of ChatGPTcited by 268
  3. 2023A Categorical Archive of ChatGPT Failurescited by 168
  4. 2023How well do Large Language Models perform in Arithmetic tasks?cited by 130
  5. 2023A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasetscited by 123
  6. 2023Evaluating GPT-4 and ChatGPT on Japanese Medical Licensing Examinationscited by 63
  7. 2023An Independent Evaluation of ChatGPT on Mathematical Word Problems (MWP)cited by 31
  8. 2023ChatGPT Participates in a Computer Science Examcited by 19
  9. 2023ChatGPT is a Remarkable Tool -- For Expertscited by 16
  10. 2023Performance of ChatGPT on the US Fundamentals of Engineering Exam: Comprehensive Assessment of Proficiency and Potential Implications for Professional Environmental Engineering Practicecited by 15
  11. 2023Can ChatGPT Pass An Introductory Level Functional Language Programming Course?cited by 9
  12. 2023Industrial Engineering with Large Language Models: A case study of ChatGPT's performance on Oil & Gas problemscited by 7
4 more
  1. 2023Analyzing ChatGPT's Aptitude in an Introductory Computer Engineering Coursecited by 5
  2. 2023Humans are Still Better than ChatGPT: Case of the IEEEXtreme Competitioncited by 5
  3. 2023Chatbots put to the test in math and logic problems: A preliminary comparison and assessment of ChatGPT-3.5, ChatGPT-4, and Google Bardcited by 3
  4. 2023Cognitive network science reveals bias in GPT-3, ChatGPT, and GPT-4 mirroring math anxiety in high-school studentscited by 2

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