ChatGPT-Based Preparation Tool for Industrial Engineer Certification Examinations

This study aims to evaluate the performance of artificial intelligence language models in the Industrial Engineer Certification Examination ‎and to analyze their accuracy across different subjects. A total of 750 past exam questions (from 2019 to 2024) across five subjects, namely ‎Quality Management, Production and Operations Management, Operations Research, Engineering Economics, and Human Factors ‎Engineering, were tested using ChatGPT-3.5 and ChatGPT-4o. The models’ responses were compared with standard answers to compute ‎accuracy rates and identify performance differences. Additionally, the Chain of Thought (CoT) and Tree of Thought (ToT) reasoning ‎frameworks were applied to incorrect responses from GPT-4o to assess improvements in reasoning. The results show that ChatGPT-4o ‎achieved significantly higher accuracy and reasoning coherence than ChatGPT-3.5, particularly in Quality Management and Production ‎Management. Overall, this study demonstrates the potential of generative AI as an effective tool for professional education and exam ‎preparation, offering insights for future model optimization and educational integration‎.

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Publication Details

Journal
International Journal of Basic and Applied Sciences
Published
2026-01-09
DOI
https://doi.org/10.14419/vet88k67
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

ChatGPT-Based Preparation Tool for Industrial Engineer Certification Examinations

Chen-Chi Wang, Yung-Chun Chang, Chun-Ying Lin, Jui-Chan Huang et al.
International Journal of Basic and Applied Sciences
Artificial Intelligence in Healthcare and Education
article

ChatGPT-Based Preparation Tool for Industrial Engineer Certification Examinations

Chen-Chi Wang, Yung-Chun Chang, Chun-Ying Lin, Jui-Chan Huang, Cheng-Wen Chang
article en

Abstract

This study aims to evaluate the performance of artificial intelligence language models in the Industrial Engineer Certification Examination ‎and to analyze their accuracy across different subjects. A total of 750 past exam questions (from 2019 to 2024) across five subjects, namely ‎Quality Management, Production and Operations Management, Operations Research, Engineering Economics, and Human Factors ‎Engineering, were tested using ChatGPT-3.5 and ChatGPT-4o. The models’ responses were compared with standard answers to compute ‎accuracy rates and identify performance differences. Additionally, the Chain of Thought (CoT) and Tree of Thought (ToT) reasoning ‎frameworks were applied to incorrect responses from GPT-4o to assess improvements in reasoning. The results show that ChatGPT-4o ‎achieved significantly higher accuracy and reasoning coherence than ChatGPT-3.5, particularly in Quality Management and Production ‎Management. Overall, this study demonstrates the potential of generative AI as an effective tool for professional education and exam ‎preparation, offering insights for future model optimization and educational integration‎.

International Journal of Basic and Applied SciencesVol. 15(1)
National Kaohsiung First University of Science and Technology (TW), University of Science and Technology (YE), National University of Kaohsiung (TW), National Kaohsiung University of Applied Sciences (TW)
National Science and Technology Council
Openalex Percentile: Top 93%
Artificial Intelligence in Healthcare and Education
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