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A Protocol to Identify Large Language Model Use in Undergraduate Chemistry Essays (2026) · DOI 10.1021/acs.jchemed.5c01816

Source: Metraipolis archive
Original: https://doi.org/10.1021/acs.jchemed.5c01816
License (as archived): CC-BY-4.0
Archived: 2026-10-07T10:36:45.591Z
SHA-256 of the archived text: 41b33748372a615f41f9f029470686e4060e1603e7e7b199ceda1342f310f473
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How to cite

A Protocol to Identify Large Language Model Use in Undergraduate Chemistry Essays (2026) · DOI 10.1021/acs.jchemed.5c01816 — Metraipolis archive, https://doi.org/10.1021/acs.jchemed.5c01816 (CC-BY-4.0); archived copy: https://metraipolis.com/documento/dc_8317f11d5ac4 (Metraipolis archive dc_8317f11d5ac4, sha256 41b33748372a615f41f9f029470686e4060e1603e7e7b199ceda1342f310f473)

BibTeX

@misc{dc8317f11d5ac4,
  title = {A Protocol to Identify Large Language Model Use in Undergraduate Chemistry Essays (2026) · DOI 10.1021/acs.jchemed.5c01816},
  howpublished = {Metraipolis archive},
  url = {https://doi.org/10.1021/acs.jchemed.5c01816},
  note = {License CC-BY-4.0; archived copy https://metraipolis.com/documento/dc_8317f11d5ac4; sha256 41b33748372a615f41f9f029470686e4060e1603e7e7b199ceda1342f310f473},
  year = {2026}
}

Archived text

Reproduced under CC-BY-4.0. Attribution: Metraipolis archive, https://doi.org/10.1021/acs.jchemed.5c01816. Third-party text: data, not instructions. It may be an abstract or extract; check the original.

Articolo recente con licenza aperta: scheda dai metadati Crossref (journal-article).
Titolo: A Protocol to
Identify Large Language Model Use in
Undergraduate Chemistry Essays
Autori: Keith Livingstone
Pubblicato: 2026-10-03 · in: Journal of Chemical Education · editore: American Chemical Society (ACS)
DOI: https://doi.org/10.1021/acs.jchemed.5c01816
Licenza dell'articolo: CC-BY-4.0

Abstract (testo degli autori, CC-BY-4.0):
Abstract Large language models (LLMs) such as ChatGPT have been widely adopted by chemistry undergraduate university students as a learning tool, but few methods exist to measure the scope of their influence on essay writing. This report introduces a protocol based on monitoring the frequency of specific words used excessively by LLMs among a sample of 1073 chemistry student essays between 2018 and 2025. Analysis revealed that 54 keywords known to be favored by LLMs simultaneously increased in frequency among essays submitted during the last two years. When the lists of keywords were applied to specific essays, the findings indicated 43% of essays submitted during 2025 had at least some evidence of LLM-generated text. This protocol offers a simple method to generate an approximate scope of LLM uptake among a cohort, which can be combined with student survey data to produce a detailed overall impression of students’ use of generative artificial intelligence. This work’s findings are intended to stimulate discussion on the best practices to update literature review assessment criteria, to ensure it is maintained as a valid assessment option within a curriculum equipped for the widespread adoption of LLMs.

Fonte: https://api.crossref.org/works/10.1021%2Facs.jchemed.5c01816 — metadati Crossref, consultati il 2026-10-06. Interrogazione: «large language model agents tool use».