Artificial Intelligence or Nursing Student? Revisiting Clues in the Connectives.

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
ACS Applied Bio Materials Pub Date : 2024-11-01 Epub Date: 2024-07-05 DOI:10.1097/NNE.0000000000001696
Miriam R Bowers Abbott, Wyatt W Abbott
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引用次数: 0

Abstract

Background: Recent research at a single-purpose nursing institution has suggested a means to authenticate student writing by distinguishing it from artificial intelligence (AI)-generated text through the detection of key terms.

Purpose: The purpose was to replicate and expand the research that identified key terms present in student writing but absent from AI-generated text.

Methods: A total of 5 generative AI writing tools were fed prompts to collect 14 787 words. Using the Search function on word processing software, the frequency of the terms, because, since, so, then, thing, think , and too , was measured and compared against earlier published findings from AI and students.

Results: The replication study was successful for the terms since, then, thing, think, and too.

Conclusions: Measuring key term frequency may be a path to authenticate student writing. While no tool can provide certainty of original authorship, the absence of key terms in a student submission may suggest AI authorship.

人工智能还是护理专业学生?重新审视连接词中的线索。
背景:最近在一家单一目的护理机构进行的研究提出了一种方法,通过检测关键术语将学生写作与人工智能(AI)生成的文本区分开来,从而鉴定学生写作的真伪:方法:共向 5 个人工智能生成的写作工具提供提示,收集了 14 787 个单词。使用文字处理软件的搜索功能,测量了 "因为"、"因为"、"所以"、"那么"、"事情"、"认为 "和 "也 "等词语的出现频率,并将其与人工智能和学生早期发表的研究结果进行了比较:结果:对 "因为"、"那么"、"事情"、"认为 "和 "也 "等词的复制研究取得了成功:测量关键词语的使用频率可能是鉴定学生写作的一条途径。虽然没有任何工具可以确定作者是原创者,但如果学生提交的文章中没有关键术语,则可能表明作者是人工智能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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