The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Artificial Intelligence and Authorship Editor Policy: ChatGPT, Bard Bing AI, and beyond.
Abstract
Artificial intelligence and large-language model chatbots have generated significant attention in higher education, and in research practice. Whether ChatGPT, Bard, Jasper Chat, Socratic, Bing AI, DialoGPT, or something else, these are all shaping how education and research occur. In this Editorial, we offer five editorial principles to guide decision-making for editors, which will also become policy for the Journal of University Teaching and Learning Practice. First, we articulate that non-human authorship does not constitute authorship. Second, artificial intelligence should be leveraged to support authors. Third, artificial intelligence can offer useful feedback and pre-review. Fourth, transparency of artificial intelligence usage is an expectation. And fifth, the use of AI in research design, conduct, and dissemination must comply with established ethical principles. In these five principles, we articulate a position of optimism for the new forms of knowledge and research we might garner. We see AI as a mechanism that may augment our current practices but will not likely replace all of them. However, we do issue caution to the limitations of large language models including possible proliferation of poor-quality research, Stochastic Parroting, and data hallucinations. As with all research, authors should be comfortably familiar with the underlying methods being used to generate data and should ensure a clear understanding of the AI tools being used prior to deployment for research.
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“To this point, some academic journals are encouraging the use of AI to refine manuscripts and edit papers, provided that the technology’s contribution is appropriately recognised ( Crawford et al., 2023).”
From Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis (2024) · cites this paper as Crawford et al., 2023
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Cites
Generating scholarly content with ChatGPT: Ethical challenges for medical publishing
Liebrenz, M., Schleifer, R., Buadze, A., Bhugra, D., & Smith, A. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00019-5 · Cited by 594
Research works printed but not linked: 23
- Awdry, R., Dawson, P., & Sutherland-Smith, W. (2022). Contract cheating: To legislate or not to legislate-is that the question?. Assessment & Evaluation in Higher Education, 47(5), 712-726.
- Azamfirei, R., Kudchadkar, S., & Fackler, J. (2023). Large language models and the perils of their hallucinations. Critical Care, 27(1), 1-2.
- Bender, E., Gebru, T., McMillan-Major, A., & Shmitchell, S. (2021, March). On the Dangers of Stochastic Parrots: Can Language Models Be Too Big?. In Proceedings of the 2021 ACM conference on fairness, accountability, and transparency (pp. 610-623).
- Booten, K. (2020). Making Writing Harder: Computer-Mediated Authorship and the Problem of Care. Proceedings of ELO2020, Orlando.
- Crawford, J., Cowling, M., & Allen, K. A. (2023). Leadership is needed for ethical ChatGPT: Character, assessment, and learning using artificial intelligence (AI). Journal of University Teaching & Learning Practice, 20(3), 02. https://doi.org/10.53761/1.20.3.02 · DOI · Paper page
- Dawson, P. (2020). Cognitive offloading and assessment. In M. Bearman, P. Dawson, R. Ajjawi, J. Tai & D. Boud (eds), Reimaging University Assessment in a Digital World (37-48). Springer.
- Dawson, P., & Sutherland-Smith, W. (2018). Can markers detect contract cheating? Results from a pilot study. Assessment & Evaluation in Higher Education, 43(2), 286-293.
- Eager, B., & Brunton, R. (2023). Prompting higher education towards AI-augmented teaching and learning practice. Journal of University Teaching and Learning Practice, 20(5), https://doi.org/https://doi.org/10.53761/1.20.5.02 · DOI · Paper page
- Felzmann, H., Villaronga, E. F., Lutz, C., & Tamò-Larrieux, A. (2019). Transparency you can trust: Transparency requirements for artificial intelligence between legal norms and contextual concerns. Big Data & Society, 6(1). https://doi.org/10.1177/2053951719860542 · DOI
- Hamzaçebi, C., Akay, D., & Kutay, F. (2009). Comparison of direct and iterative artificial neural network forecast approaches in multi-periodic time series forecasting. Expert Systems With Applications, 36(2), 3839-3844.
- King, M., & ChatGPT. (2023). A conversation on artificial intelligence, chatbots, and plagiarism in higher education. Cellular and Molecular Bioengineering, 16(1), 1-2. https://doi.org/10.1007/s12195-022-00754-8 · DOI · Paper page
- Lacasse, J. R., & Leo, J. (2010). Ghostwriting at elite academic medical centers in the United States. PLoS Medicine, 7(2), e1000230.
- Lodge, J. M., Thompson, K., & Corrin, L. (2023). Mapping out a research agenda for generative artificial intelligence in tertiary education. Australasian Journal of Educational Technology, 39(1), 1-8.
- Perkins, M. (2023). Academic integrity considerations of AI Large Language Models in the post- pandemic era: ChatGPT and beyond. Journal of University Teaching & Learning Practice, 20(2), 07.
- Education and Information Technologies (2021). Retraction Note: Education and Information Technologies. Education and Information Technologies, 26, 7307-7319. https://doi.org/10.1007/s10639-021-10588-y · DOI
- Rudolph, J., Tan, S., & Tan, S. (2023). ChatGPT: Bullshit spewer or the end of traditional assessments in higher education? Journal of Applied Learning & Teaching, 6(1), 1-22. https://doi.org/10.37074/jalt.2023.6.1.9 · DOI · Paper page
- Samuel, A. (1960). Some moral and technical consequences of automation-a refutation. Science, 132(3429), 741-742.
- Srivastava, M. (2023, February 17). A day in the life of ChatGPT as an academic reviewer: Investigating the potential of large language model for scientific literature review. OSF preprints. https://doi.org/10.31219/osf.10/wydct Stokel-Walker, C. (2023). ChatGPT listed as author on research papers. Nature, 613, 620-621. · DOI
- Sullivan, M., Kelly, A., McLaughlan, P. (2023). ChatGPT in higher education: Consideration for academic integrity and student learning. Journal of Applied Learning & Teaching, 6(1). https://doi.org/10.37074/jalt.2023.6.1.17 · DOI · Paper page
- Thorp, H. H. (2023). ChatGPT is fun, but not an author. Science, 379(6630), 313-313.
- van Dis, E. A., Bollen, J., Zuidema, W., van Rooij, R., & Bockting, C. L. (2023). ChatGPT: Five priorities for research. Nature, 614(7947), 224-226. https://doi.org/10.1038/d41586-023- 00288-7 · DOI · Paper page
- Xames, M. D. & Shefa, J. (2023) ChatGPT for research and publication: Opportunities and challenges. Journal of Applied Learning & Teaching, 6(1), 1-6. https://doi.org/10.37074/jalt.2023.6.1.20 · DOI
- Woods, M., Paulus, T., Atkins, D. P., & Macklin, R. (2016). Advancing qualitative research using qualitative data analysis software (QDAS)? Reviewing potential versus practice in published studies using ATLAS. ti and NVivo, 1994-2013. Social Science Computer Review, 34(5), 597-617.
Cited by
Nguyen, A., Kremantzis, M., Essien, A., Petrounias, I., & Hosseini, S. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/caraaq92 · Cited by 146
Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania
Rudolph, J., Mohamed Ismail, F. M., & Popenici, S. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/54fs5e77 · Cited by 189
Academic publisher guidelines on AI usage: A ChatGPT supported thematic analysis
Perkins, M., & Roe, J. (2024) · F1000Research · doi:10.12688/f1000research.142411.2 · Cited by 123
Editorial: Artificial Intelligence is Awesome, but Good Teaching Should Always Come First.
Crawford, J., Vallis, C., Yang, J., Fitzgerald, R., O'Dea, C., & Cowling, M. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/1.20.7.01 · Cited by 18
Self-citationLimna, P., & Kraiwanit, T. (2024) · Journal of University Teaching and Learning Practice · doi:10.53761/7zmssq60 · Cited by 13
Metadata
- Authors
- Crawford, J., Cowling, M., Ashton-Hay, S., Kelder, J.-A., Middleton, R., & Wilson, G.
- Venue
- Journal of University Teaching and Learning Practice
- Publisher
- Open Access Publishing Association
- Published
- 2023-09-03
- Volume
- 20
- Issue
- 5
- ISSN
- 1449-9789
- Cited by
- 36
- References
- 1
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.