{"title":"人工智能还是护理专业学生?重新审视连接词中的线索。","authors":"Miriam R Bowers Abbott, Wyatt W Abbott","doi":"10.1097/NNE.0000000000001696","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>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.</p><p><strong>Purpose: </strong>The purpose was to replicate and expand the research that identified key terms present in student writing but absent from AI-generated text.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>The replication study was successful for the terms since, then, thing, think, and too.</p><p><strong>Conclusions: </strong>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.</p>","PeriodicalId":54706,"journal":{"name":"Nurse Educator","volume":" ","pages":"306-309"},"PeriodicalIF":2.8000,"publicationDate":"2024-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Artificial Intelligence or Nursing Student? Revisiting Clues in the Connectives.\",\"authors\":\"Miriam R Bowers Abbott, Wyatt W Abbott\",\"doi\":\"10.1097/NNE.0000000000001696\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>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.</p><p><strong>Purpose: </strong>The purpose was to replicate and expand the research that identified key terms present in student writing but absent from AI-generated text.</p><p><strong>Methods: </strong>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.</p><p><strong>Results: </strong>The replication study was successful for the terms since, then, thing, think, and too.</p><p><strong>Conclusions: </strong>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.</p>\",\"PeriodicalId\":54706,\"journal\":{\"name\":\"Nurse Educator\",\"volume\":\" \",\"pages\":\"306-309\"},\"PeriodicalIF\":2.8000,\"publicationDate\":\"2024-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nurse Educator\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1097/NNE.0000000000001696\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/5 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"NURSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nurse Educator","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/NNE.0000000000001696","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/5 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"NURSING","Score":null,"Total":0}
Artificial Intelligence or Nursing Student? Revisiting Clues in the Connectives.
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.
期刊介绍:
Nurse Educator, a scholarly, peer reviewed journal for faculty and administrators in schools of nursing and nurse educators in other settings, provides practical information and research related to nursing education. Topics include program, curriculum, course, and faculty development; teaching and learning in nursing; technology in nursing education; simulation; clinical teaching and evaluation; testing and measurement; trends and issues; and research in nursing education.