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Mike Perkins; Jasper Roe; Darius Postma; James McGaughran; Don Hickerson – Journal of Academic Ethics, 2024
This study explores the capability of academic staff assisted by the Turnitin Artificial Intelligence (AI) detection tool to identify the use of AI-generated content in university assessments. 22 different experimental submissions were produced using Open AI's ChatGPT tool, with prompting techniques used to reduce the likelihood of AI detectors…
Descriptors: Artificial Intelligence, Student Evaluation, Identification, Natural Language Processing
Natalie V. Covington; Olivia Vruwink – International Journal of Artificial Intelligence in Education, 2025
ChatGPT and other large language models (LLMs) have the potential to significantly disrupt common educational practices and assessments, given their capability to quickly generate human-like text in response to user prompts. LLMs GPT-3.5 and GPT-4 have been tested against many standardized and high-stakes assessment materials (e.g. SAT, Uniform…
Descriptors: Artificial Intelligence, Technology Uses in Education, Undergraduate Study, Introductory Courses
Brian W. Stone – Teaching of Psychology, 2025
Background: Students in higher education are using generative artificial intelligence (AI) despite mixed messages and contradictory policies. Objective: This study helps answer outstanding questions about many aspects of AI in higher education: familiarity, usage, perceptions of peers, ethical/social views, and AI grading. Method: I surveyed 733…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Brady D. Lund; Tae Hee Lee; Nishith Reddy Mannuru; Nikhila Arutla – Journal of Academic Ethics, 2025
The emergence of generative artificial intelligence tools, such as ChatGPT, presents new challenges impacting student perceptions of academic integrity. While extensive research exists on academic misconduct and student perceptions of various infractions, there is limited understanding of how AI tools impact these views and whether their use…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Student Attitudes
Hung Manh Nguyen; Daisaku Goto – Education and Information Technologies, 2024
The proliferation of artificial intelligence (AI) technology has brought both innovative opportunities and unprecedented challenges to the education sector. Although AI makes education more accessible and efficient, the intentional misuse of AI chatbots in facilitating academic cheating has become a growing concern. By using the indirect…
Descriptors: Academic Achievement, Cheating, Student Behavior, Artificial Intelligence
Ibrahim Adeshola; Adeola Praise Adepoju – Interactive Learning Environments, 2024
The launch of OpenAI ChatGPT's language-generation model has raised alarms within many sectors, especially the academic sector. Several academicians have urged universities to develop new forms of assessment after the launch of ChatGPT, which solves academic questions in less than a few minutes. Academic cheating is not a new phenomenon, and the…
Descriptors: Opportunities, Barriers, Artificial Intelligence, Natural Language Processing
Tobias Kohn – Journal of Computer Assisted Learning, 2025
Background: The recent advent of powerful, exam-passing large language models (LLMs) in public awareness has led to concerns over students cheating, but has also given rise to calls for including or even focusing education on LLMs. There is a perceived urgency to react immediately, as well as claims that AI-based reforms of education will lead to…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Usability
Lancaster, Thomas – Journal of Academic Ethics, 2021
Is academic integrity research presented from a positive integrity standpoint? This paper uses Natural Language Processing (NLP) techniques to explore a data set of 8,507 academic integrity papers published between 1904 and 2019.Two main techniques are used to linguistically examine paper titles: (1) bigram (word pair) analysis and (2) sentiment…
Descriptors: Cheating, Integrity, Natural Language Processing, Educational Research
David R. Firth; Mason Derendinger; Jason Triche – Information Systems Education Journal, 2024
In this paper we describe a framework for teaching students when they should, or should not use generative AI such as ChatGPT. Generative AI has created a fundamental shift in how students can complete their class assignments, and other tasks such as building resumes and creating cover letters, and we believe it is imperative that we teach…
Descriptors: Cheating, Artificial Intelligence, Man Machine Systems, Natural Language Processing
Matthew Landers – Higher Education for the Future, 2025
This article presents a brief overview of the state-of-the-art in large language models (LLMs) like ChatGPT and discusses the difficulties that these technologies create for educators with regard to assessment. Making use of the 'arms race' metaphor, this article argues that there are no simple solutions to the 'AI problem'. Rather, this author…
Descriptors: Ethics, Cheating, Plagiarism, Artificial Intelligence
Debby R. E. Cotton; Peter A. Cotton; J. Reuben Shipway – Innovations in Education and Teaching International, 2024
The use of artificial intelligence in academia is a hot topic in the education field. ChatGPT is an AI tool that offers a range of benefits, including increased student engagement, collaboration, and accessibility. However, is also raises concerns regarding academic honesty and plagiarism. This paper examines the opportunities and challenges of…
Descriptors: Integrity, Cheating, Artificial Intelligence, Man Machine Systems
Amanda Light Dunbar; Sandra Chang-Kredl – Changing English: Studies in Culture and Education, 2025
Long before ChatGPT, it was an open secret that students did not always read the books they were assigned in their English Language Arts (ELA) classes, relying instead on online study guides like SparkNotes. Via a retrospective survey, our exploratory study examined (1) the rate of SparkNotes use among high-school ELA students; (2) why students…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Arts
Chukwuemeka Ihekweazu; Bing Zhou; Elizabeth Adepeju Adelowo – Information Systems Education Journal, 2024
This study delves into the opportunities and challenges associated with the deployment of AI tools in the education sector. It systematically explores the potential benefits and risks inherent in utilizing these tools while specifically addressing the complexities of identifying and preventing academic dishonesty. Recognizing the ethical…
Descriptors: Ethics, Artificial Intelligence, Responsibility, Technology Uses in Education
Edmund De Leon Evangelista – Contemporary Educational Technology, 2025
The rapid advancement of artificial intelligence (AI) technologies, particularly OpenAI's ChatGPT, has significantly impacted higher education institutions (HEIs), offering opportunities and challenges. While these tools enhance personalized learning and content generation, they threaten academic integrity, especially in assessment environments.…
Descriptors: Artificial Intelligence, Integrity, Educational Strategies, Natural Language Processing
Josh Freeman – Higher Education Policy Institute, 2024
This new Policy Note by HEPI and Kortext explores students' attitudes to AI. Based on a poll of 1,250 students through UCAS, we build a picture of the way students use and view generative AI technologies like ChatGPT and Google Bard. We find that the use of generative AI has become normalised in higher education, but that universities have so far…
Descriptors: Undergraduate Students, Artificial Intelligence, Man Machine Systems, Natural Language Processing

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