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Prospects and epistemic challenges for using Chat Generative Pre-trained Transformers in higher education evaluation

by Lucas Pedro 1,*
1
Hospital das Clínicas da Universidade de São Paulo, São Paulo, Brazil
*
Author to whom correspondence should be addressed.
Received: 27 February 2024 / Accepted: 11 March 2024 / Published Online: 12 March 2024

Abstract

Every academic institution is shaken by the recent development of Chat Generative Pre-trained Transformer, and although we still don't fully grasp all of its potential and hazards, it is worthwhile to offer some first analysis. Academic prospects for Chat Generative Pre-trained Transformer are unparalleled because of its remarkable human-like skills, which outperform the majority of recently released tools. Over the past few months, Chat Generative Pre-trained Transformer has received extraordinary interest from the news and academic community (as of 23/02/2023, there were 650,000,000 results in a Google search for the term). Since it is unlikely that the chatbot was designed with the intention of serving as a stand-in for academic writing, its use in academic writing is a byproduct of clever artificial intelligence. If given the chance, students everywhere would find a way around assessments, thus we are all worried that some students would take advantage of it despite its advantages. Although there isn't now a problem involving assessment integrity in academics, it is impossible to overlook the development of powerful artificial intelligence and tools that could facilitate cheating. Some of us think that the use of Chat Generative Pre-trained Transformer in assessments has some epistemic consequences; yet, these risks do not indicate that we will give up. Although we now know that certain university programs—like management studies and information technology—have a higher risk of academic dishonesty, educators are not new to the practice; rather, they are still learning about Chat Generative Pre-trained Transformer. I don't see any strong arguments in favor of allowing its usage in assessments, even though it is unavoidable in certain academic contexts. Instead than teaching students to "copy and paste," they teach them to "think and write critically." Therefore, the fact that Chat Generative Pre-trained Transformer passed the MBA and medical school exams should raise red flags.


Copyright: © 2024 by Pedro. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (Creative Commons Attribution 4.0 International License). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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ACS Style
Pedro, L. Prospects and epistemic challenges for using Chat Generative Pre-trained Transformers in higher education evaluation. International Journal of Clinical Medical Research, 2024, 2, 25. https://doi.org/https://doi.org/https://doi.org/10.61466/ijcmr2020005
AMA Style
Pedro L. Prospects and epistemic challenges for using Chat Generative Pre-trained Transformers in higher education evaluation. International Journal of Clinical Medical Research; 2024, 2(2):25. https://doi.org/https://doi.org/https://doi.org/10.61466/ijcmr2020005
Chicago/Turabian Style
Pedro, Lucas 2024. "Prospects and epistemic challenges for using Chat Generative Pre-trained Transformers in higher education evaluation" International Journal of Clinical Medical Research 2, no.2:25. https://doi.org/https://doi.org/https://doi.org/10.61466/ijcmr2020005

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References

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