{"title":"发现异常:探索定性研究对人工智能辅助作文教学中识别人工智能生成文本的影响","authors":"Ali Garib , Tina A. Coffelt","doi":"10.1016/j.compcom.2024.102869","DOIUrl":null,"url":null,"abstract":"<div><p>This study inspires new pedagogical practices with evolving technological innovations. One example of such innovation is the emergence of artificial intelligence (AI) in education. The potential impact of generative AI, such as ChatGPT, on composition education has caused concerns among educators due to its human-like writing capabilities. However, there is no escape from ChatGPT-generated text, which is influenced by prompt engineering. Such engineering can lead to underlying issues in content, prompting a pedagogical opportunity for understanding human-written and AI-generated texts. Since, to this date, there is no single reliable source for identifying AI-generated text, this study introduces a pedagogical approach, DETECT, with two major goals: (1) explore the nuances that differentiate human expression from the algorithmic patterns and tendencies of generative AI writing and (2) inspire ways to integrate generative AI in composition instruction in a post-plagiarism era. Using exploratory practice research, this article examines DETECT in composition instruction of 32 students during Fall 2023 and Spring 2024. The findings showed that using DETECT improved students’ confidence in analyzing human-written and AI-generated texts, which enhanced their recognition and appreciation of their own writing voice. The study concludes with pedagogical implications for the possibilities of generative AI in writing instruction.</p></div>","PeriodicalId":35773,"journal":{"name":"Computers and Composition","volume":"73 ","pages":"Article 102869"},"PeriodicalIF":0.0000,"publicationDate":"2024-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"DETECTing the anomalies: Exploring implications of qualitative research in identifying AI-generated text for AI-assisted composition instruction\",\"authors\":\"Ali Garib , Tina A. Coffelt\",\"doi\":\"10.1016/j.compcom.2024.102869\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This study inspires new pedagogical practices with evolving technological innovations. One example of such innovation is the emergence of artificial intelligence (AI) in education. The potential impact of generative AI, such as ChatGPT, on composition education has caused concerns among educators due to its human-like writing capabilities. However, there is no escape from ChatGPT-generated text, which is influenced by prompt engineering. Such engineering can lead to underlying issues in content, prompting a pedagogical opportunity for understanding human-written and AI-generated texts. Since, to this date, there is no single reliable source for identifying AI-generated text, this study introduces a pedagogical approach, DETECT, with two major goals: (1) explore the nuances that differentiate human expression from the algorithmic patterns and tendencies of generative AI writing and (2) inspire ways to integrate generative AI in composition instruction in a post-plagiarism era. Using exploratory practice research, this article examines DETECT in composition instruction of 32 students during Fall 2023 and Spring 2024. The findings showed that using DETECT improved students’ confidence in analyzing human-written and AI-generated texts, which enhanced their recognition and appreciation of their own writing voice. The study concludes with pedagogical implications for the possibilities of generative AI in writing instruction.</p></div>\",\"PeriodicalId\":35773,\"journal\":{\"name\":\"Computers and Composition\",\"volume\":\"73 \",\"pages\":\"Article 102869\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Computers and Composition\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S875546152400046X\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Arts and Humanities\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Computers and Composition","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S875546152400046X","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Arts and Humanities","Score":null,"Total":0}
DETECTing the anomalies: Exploring implications of qualitative research in identifying AI-generated text for AI-assisted composition instruction
This study inspires new pedagogical practices with evolving technological innovations. One example of such innovation is the emergence of artificial intelligence (AI) in education. The potential impact of generative AI, such as ChatGPT, on composition education has caused concerns among educators due to its human-like writing capabilities. However, there is no escape from ChatGPT-generated text, which is influenced by prompt engineering. Such engineering can lead to underlying issues in content, prompting a pedagogical opportunity for understanding human-written and AI-generated texts. Since, to this date, there is no single reliable source for identifying AI-generated text, this study introduces a pedagogical approach, DETECT, with two major goals: (1) explore the nuances that differentiate human expression from the algorithmic patterns and tendencies of generative AI writing and (2) inspire ways to integrate generative AI in composition instruction in a post-plagiarism era. Using exploratory practice research, this article examines DETECT in composition instruction of 32 students during Fall 2023 and Spring 2024. The findings showed that using DETECT improved students’ confidence in analyzing human-written and AI-generated texts, which enhanced their recognition and appreciation of their own writing voice. The study concludes with pedagogical implications for the possibilities of generative AI in writing instruction.
期刊介绍:
Computers and Composition: An International Journal is devoted to exploring the use of computers in writing classes, writing programs, and writing research. It provides a forum for discussing issues connected with writing and computer use. It also offers information about integrating computers into writing programs on the basis of sound theoretical and pedagogical decisions, and empirical evidence. It welcomes articles, reviews, and letters to the Editors that may be of interest to readers, including descriptions of computer-aided writing and/or reading instruction, discussions of topics related to computer use of software development; explorations of controversial ethical, legal, or social issues related to the use of computers in writing programs.