A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education
By Michael R. King, ChatGPT. Cellular and Molecular Bioengineering, 2023
511 citations recorded by the source corpus.
Subfields: Health Informatics
View Paper: https://www.semanticscholar.org/paper/288078127a3078332230442170f6745ed333c700
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In Health Informatics
Citations in the corpus
- ChatGPT and large language models in academia: opportunities and challenges (2023, background): “In a third example, a researcher presents the results of a conversation with ChatGPT around AI, chatbots using LLMs, and plagiarism in higher education [8].”
- ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations (2023, background): “, 2023), plagiarism (Biswas, 2023; King and ChatGPT, 2023), and more which are presented in more detail later in this paper.”
- ChatGPT and a new academic reality: Artificial Intelligence‐written research papers and the ethics of the large language models in scholarly publishing (2023, methodology): “While ChatGPT may be able to provide in-text references in future versions, it is important to consider the potential consequences of relying solely on an automated tool like ChatGPT instead of reviewing the literature in depth (King, 2023).”
- What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education (2023, background): “In this context, recent studies on ChatGPT also support our argument that although there are negative sides to adopting ChatGPT, it also presents educational opportunities which can be leveraged, for instance, to improve instruction delivery and learning (Kasneci et al., 2023; King & chatGPT, 2023).”
- ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health (2023, background): “For example, ChatGPT has been listed as the first author of four papers, (26, 40, 41, 42) without considering the possibility of “involuntary plagiarism” or intellectual property issues surrounding the output of the model.”