| dc.description.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. | vi |
