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Yong Tat Lim
University of Technology Sarawak, Malaysia

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Journal : Journal of Civil Engineering

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LEARNING ABOUT CONCRETE-FILLED TUBE USING CHATGPT Jen Hua Ling; Yong Tat Lim; Wen Kam Leong; How Teck Sia
Journal of Civil Engineering Vol 38, No 1 (2023)
Publisher : Institut Teknologi Sepuluh Nopember

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12962/j20861206.v38i1.16470

Abstract

ChatGPT is an artificial intelligence that can understand context and respond appropriately. It could be used for research on a topic. However, ChatGPT does not always provide accurate information. Its performance has not been tested in engineering fields. In this study, ChatGPT was consulted about concrete-filled tubes (CFT), which is a structural element primarily subjected to axial load. Fifty-eight questions were posted to ChatGPT. ChatGPT’s responses (370 sentences) were evaluated. ChatGPT generated plagiarism-free statements, with only a 12% Turnitin similarity index. 78.6% of ChatGPT’s sentences were long and complex. Thus, Hemingway Editor gave them a Grade 14 for poor readability. The information given by ChatGPT can be classified as correct, erroneous, contradictory, and unverified. ChatGPT could be used as a research tool, but with limitations. It can explain the basic concepts of CFT but also provide inaccurate and contradictory information. A researcher needs to be cautious while using ChatGPT in research. ChatGPT could be used to test some hypotheses or theories. However, the quality of the output is dependent on the user’s critical inputs and an in-depth conversation with ChatGPT.
Co-Authors How Teck Sia Jen Hua Ling Wen Kam Leong