{"title":"使用基于人工智能的检测器来控制ESL写作中的人工智能辅助抄袭:“终结者对机器”","authors":"Karim Ibrahim","doi":"10.1186/s40468-023-00260-2","DOIUrl":null,"url":null,"abstract":"Abstract The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted plagiarism, especially when conventional methods fail to detect AI-generated texts. One approach to managing AI-assisted plagiarism is using fine-tuned AI classifiers, such as RoBERTa, to identify machine-generated texts; however, the reliability of this approach is yet to be established. To address the challenge of AI-assisted plagiarism in ESL contexts, the present cross-disciplinary descriptive study examined the potential of two RoBERTa-based classifiers to control AI-assisted plagiarism on a dataset of 240 human-written and ChatGPT-generated essays. Data analysis revealed that both platforms could identify AI-generated texts, but their detection accuracy was inconsistent across the dataset.","PeriodicalId":37050,"journal":{"name":"Language Testing in Asia","volume":"279 1","pages":"0"},"PeriodicalIF":2.1000,"publicationDate":"2023-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Using AI-based detectors to control AI-assisted plagiarism in ESL writing: “The Terminator Versus the Machines”\",\"authors\":\"Karim Ibrahim\",\"doi\":\"10.1186/s40468-023-00260-2\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Abstract The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted plagiarism, especially when conventional methods fail to detect AI-generated texts. One approach to managing AI-assisted plagiarism is using fine-tuned AI classifiers, such as RoBERTa, to identify machine-generated texts; however, the reliability of this approach is yet to be established. To address the challenge of AI-assisted plagiarism in ESL contexts, the present cross-disciplinary descriptive study examined the potential of two RoBERTa-based classifiers to control AI-assisted plagiarism on a dataset of 240 human-written and ChatGPT-generated essays. Data analysis revealed that both platforms could identify AI-generated texts, but their detection accuracy was inconsistent across the dataset.\",\"PeriodicalId\":37050,\"journal\":{\"name\":\"Language Testing in Asia\",\"volume\":\"279 1\",\"pages\":\"0\"},\"PeriodicalIF\":2.1000,\"publicationDate\":\"2023-10-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Language Testing in Asia\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1186/s40468-023-00260-2\",\"RegionNum\":1,\"RegionCategory\":\"文学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"EDUCATION & EDUCATIONAL RESEARCH\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Language Testing in Asia","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1186/s40468-023-00260-2","RegionNum":1,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"EDUCATION & EDUCATIONAL RESEARCH","Score":null,"Total":0}
Using AI-based detectors to control AI-assisted plagiarism in ESL writing: “The Terminator Versus the Machines”
Abstract The release of ChatGPT marked the beginning of a new era of AI-assisted plagiarism that disrupts traditional assessment practices in ESL composition. In the face of this challenge, educators are left with little guidance in controlling AI-assisted plagiarism, especially when conventional methods fail to detect AI-generated texts. One approach to managing AI-assisted plagiarism is using fine-tuned AI classifiers, such as RoBERTa, to identify machine-generated texts; however, the reliability of this approach is yet to be established. To address the challenge of AI-assisted plagiarism in ESL contexts, the present cross-disciplinary descriptive study examined the potential of two RoBERTa-based classifiers to control AI-assisted plagiarism on a dataset of 240 human-written and ChatGPT-generated essays. Data analysis revealed that both platforms could identify AI-generated texts, but their detection accuracy was inconsistent across the dataset.