The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.
ChatGPT: Bullshit spewer or the end of traditional assessments in higher education?
Open accessAbstract
ChatGPT is the world’s most advanced chatbot thus far. Unlike other chatbots, it can create impressive prose within seconds, and it has created much hype and doomsday predictions when it comes to student assessment in higher education and a host of other matters. ChatGPT is a state-of-the-art language model (a variant of OpenAI’s Generative Pretrained Transformer (GPT) language model) designed to generate text that can be indistinguishable from text written by humans. It can engage in conversation with users in a seemingly natural and intuitive way. In this article, we briefly tell the story of OpenAI, the organisation behind ChatGPT. We highlight the fundamental change from a not-for-profit organisation to a commercial business model. In terms of our methods, we conducted an extensive literature review and experimented with this artificial intelligence (AI) software. Our literature review shows our review to be amongst the first peer-reviewed academic journal articles to explore ChatGPT and its relevance for higher education (especially assessment, learning and teaching). After a description of ChatGPT’s functionality and a summary of its strengths and limitations, we focus on the technology’s implications for higher education and discuss what is the future of learning, teaching and assessment in higher education in the context of AI chatbots such as ChatGPT. We position ChatGPT in the context of current Artificial Intelligence in Education (AIEd) research, discuss student-facing, teacher-facing and system-facing applications, and analyse opportunities and threats. We conclude the article with recommendations for students, teachers and higher education institutions. Many of them focus on assessment.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The advent of GenAI has unveiled a plethora of threats to higher education and the broader societal fabric, encompassing concerns over authorship, copyright infringement, and the potential for misuse in activities such as spamming, disseminating fake news, creating malware, and hacking (Marcus, 2023;Rudolph et al., 2023aRudolph et al., , 2023b)).”
From Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania (2024) · cites this paper as Rudolph et al., 2023a
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“It is considered by many as the most powerful AI tool ever crated [9].”
From New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“While AI technology offers promising ability for personalized learning experiences, efficient assessment, and adaptive feedback, it also presents novel challenges to the dynamics of the traditional educational bond [9].”
From New Era of Artificial Intelligence in Education: Towards a Sustainable Multifaceted Revolution (2023) · cites this paper as [9]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“The diverse learning trajectories observed in these cases illustrate how AI tools can facilitate non-linear, adaptive learning processes by enabling students to dynamically integrate new information with prior knowledge and external resources [15, 16].”
From Scaffolding Creativity: Integrating Generative AI Tools and Real-World Experiences in Business Education (2025) · cites this paper as [16]
Experimental — accuracy not yet measuredThe source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“It is more student-friendly and can provide more need-based assistance than other AWE tools, as suggested by Guo et al. (2022) and Rudolph et al. (2023).”
From Impact of ChatGPT on ESL students’ academic writing skills: a mixed methods intervention study (2024) · cites this paper as Rudolph et al. (2023)
Experimental — accuracy not yet measured
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“On the other hand, the promotion of learner autonomy and peer collaboration are similar to findings in the AWE literature (Dai et al., 2023;Rudolph et al., 2023).”
From Impact of ChatGPT on ESL students’ academic writing skills: a mixed methods intervention study (2024) · cites this paper as Rudolph et al., 2023
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“GPT-3's training on a vast corpus of 45 terabytes of text, sourced from a variety of internet-based entities like Common Crawl and Wikipedia, set a precedent for the scale of data utilised in AI development (Brown et al., 2020;Rudolph et al., 2023a).”
From Higher Education's Generative Artificial Intelligence Paradox: The Meaning of Chatbot Mania (2024) · cites this paper as Rudolph et al., 2023a
The cited source says what the claim attributes to it.
In the citing paper
“They highlight the transformative potential of generative AI in revolutionizing academic practices but also caution about its ability to facilitate academic dishonesty, such as through generating test answers [25].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [25]
The cited source says what the claim attributes to it.
In the citing paper
“They highlight the transformative potential of generative AI in revolutionizing academic practices but also caution about its ability to facilitate academic dishonesty, such as through generating test answers [25].”
From Generative AI and Academic Integrity in Higher Education: A Systematic Review and Research Agenda (2025) · cites this paper as [25]
In the citing paper
“However, concerns have been raised about ethical consideration and decreased reliability of the existing examinations.”
From Developing Medical Education Curriculum Reform Strategies to Address the Impact of Generative AI: Qualitative Study (2023) · cites this paper as [8]
In the citing paper
“On the other hand, the impact of GAI on education is disputed [6], with studies raising concerns about the ethical considerations of ChatGPT [7], evaluation practices [8], scientific integrity [9], and potential negative effects on students’ higher order thinking skills [10].”
From Developing Medical Education Curriculum Reform Strategies to Address the Impact of Generative AI: Qualitative Study (2023) · cites this paper as [8]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Language Models are Few-Shot Learners
Brown, T. B., Mann, B., Ryder, N., Subbiah, M., Kaplan, J., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · arXiv · doi:10.48550/arxiv.2005.14165 · Cited by 23,372
Searle, J. R. (1980) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00005756 · Cited by 6,954
Teaching for quality learning at university
Boulton‐Lewis, G. M. (2008) · Faculty of Education · Cited by 4,926
Kung, T. H., Cheatham, M., ChatGPT, Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., et al. (2022) · doi:10.1101/2022.12.19.22283643 · Cited by 4,115
Kung, T. H., Cheatham, M., Medenilla, A., Sillos, C., De Leon, L., Elepaño, C., Madriaga, M., Aggabao, R., Diaz-Candido, G., Maningo, J., et al. (2023) · PLOS Digital Health · doi:10.1371/journal.pdig.0000198 · Cited by 4,115
GPT-3: Its Nature, Scope, Limits, and Consequences
Floridi, L., & Chiriatti, M. (2020) · Minds and Machines · doi:10.1007/s11023-020-09548-1 · Cited by 2,519
Superintelligence: Paths, Dangers, Strategies
Robert, C. (2017) · CHANCE · doi:10.1080/09332480.2017.1302723 · Cited by 1,756
What is assessment for learning
Wiliam, D. (2011) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2011.03.001 · Cited by 1,282
Homo Deus: A Brief History of Tomorrow
Harari, Y. N. (2015) · Cited by 1,267
Gao, C. A., Howard, F. M., Markov, N. S., Dyer, E. C., Ramesh, S., Luo, Y., & Pearson, A. T. (2022) · doi:10.1101/2022.12.23.521610 · Cited by 1,099
Gao, C. A., Howard, F. M., Markov, N. S., Dyer, E. C., Ramesh, S., Luo, Y., & Pearson, A. T. (2023) · npj Digital Medicine · doi:10.1038/s41746-023-00819-6 · Cited by 1,099
Pavlik, J. V. (2023) · Journalism & Mass Communication Educator · doi:10.1177/10776958221149577 · Cited by 972
Assessment as Learning: Using Classroom Assessment to Maximize Student Learning
Earl, L. M. (2003) · Cited by 817
Machine, platform, crowd: Harnessing our digital future
Peregrina, Á. F. A. (2018) · Economía industrial · Cited by 681
ChatGPT for (Finance) research: The Bananarama Conjecture
Dowling, M., & Lucey, B. M. (2023) · Finance research letters · doi:10.1016/j.frl.2023.103662 · Cited by 648
The benefits and challenges of chatgpt: An overview
Deng, J., & Lin, Y. (2023) · Frontiers in Computing and Intelligent Systems · doi:10.54097/fcis.v2i2.4465 · Cited by 611
A Conversation on Artificial Intelligence, Chatbots, and Plagiarism in Higher Education
King, M. R., & chatGPT (2023) · Cellular and Molecular Bioengineering · doi:10.1007/s12195-022-00754-8 · Cited by 602
Viewpoint: when will AI exceed human performance? evidence from AI experts
Grace, K., Salvatier, J., Dafoe, A., Zhang, B., & Evans, O. (2018) · Journal of Artificial Intelligence Research · doi:10.1613/jair.1.11222 · Cited by 579
Peng, H., Ma, S., & Spector, J. M. (2019) · Smart Learning Environments · doi:10.1186/s40561-019-0089-y · Cited by 548
AI bot ChatGPT writes smart essays — should professors worry?
Stokel-Walker, C. (2022) · Nature · doi:10.1038/d41586-022-04397-7 · Cited by 543
Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies
Cope, B., Kalantzis, M., & Searsmith, D. (2021) · Educational Philosophy and Theory · doi:10.1080/00131857.2020.1728732 · Cited by 518
The Case for Authentic Assessment
Wiggins, G. (1990) · University of Massachusetts Amherst · doi:10.7275/ffb1-mm19 · Cited by 493
Computer-based technology and student engagement: a critical review of the literature
Schindler, L. A., Burkholder, G. J., Morad, O. A., & Marsh, C. (2017) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-017-0063-0 · Cited by 475
Koltovskaia, S. (2020) · Assessing Writing · doi:10.1016/j.asw.2020.100450 · Cited by 447
Teaching for Critical Thinking: Tools and Techniques to Help Students Question Their Assumptions
Brookfield, S. (2011) · Cited by 432
Köbis, N., & Mossink, L. D. (2021) · Computers in Human Behavior · doi:10.1016/j.chb.2020.106553 · Cited by 406
Nazari, N., Shabbir, M. S., & Setiawan, R. (2021) · Heliyon · doi:10.1016/j.heliyon.2021.e07014 · Cited by 405
OpenAI ChatGPT Generated Literature Review: Digital Twin in Healthcare
Aydın, Ö., & Karaarslan, E. (2022) · doi:10.2139/ssrn.4308687 · Cited by 391
ChatGPT: The End of Online Exam Integrity?
Susnjak, T. (2022) · arXiv · doi:10.48550/arxiv.2212.09292 · Cited by 370
How Close is ChatGPT to Human Experts? Comparison Corpus, Evaluation, and Detection
Guo, B., Zhang, X., Wang, Z., Jiang, M., Nie, J., Ding, Y., Yue, J., & Wu, Y. (2023) · arXiv · doi:10.48550/arxiv.2301.07597 · Cited by 318
Alshater, M. (2022) · SSRN Electronic Journal · doi:10.2139/ssrn.4312358 · Cited by 304
The Future of AI in Medicine: A Perspective from a Chatbot
King, M. R. (2023) · Annals of Biomedical Engineering · doi:10.1007/s10439-022-03121-w · Cited by 299
Plagiarism in the age of massive generative pre-trained transformers (GPT-3)
Dehouche, N. (2021) · Ethics in Science and Environmental Politics · doi:10.3354/esep00195 · Cited by 296
Hartmann, J., Schwenzow, J., & Witte, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4316084 · Cited by 273
Engineering Education in the Era of ChatGPT: Promise and Pitfalls of Generative AI for Education
Qadir, J. (2022) · doi:10.36227/techrxiv.21789434.v1 · Cited by 264
Grammarly as AI-powered English Writing Assistant: Students' Alternative for Writing English
Fitria, T. N. (2021) · Metathesis: Journal of English Language, Literature, and Teaching · doi:10.31002/metathesis.v5i1.3519 · Cited by 221
Artificial Intelligence as an Effective Classroom Assistant
du Boulay, B. (2016) · IEEE Intelligent Systems · doi:10.1109/mis.2016.93 · Cited by 213
How to cheat on your final paper: Assigning AI for student writing
Fyfe, P. (2023) · AI & SOCIETY · doi:10.1007/s00146-022-01397-z · Cited by 205
Can GPT-3 pass a writer’s turing test?
Elkins, K., & Chun, J. (2020) · Journal of Cultural Analytics · doi:10.22148/001c.17212 · Cited by 202
The death of the short-form physics essay in the coming AI revolution
Yeadon, W., Inyang, O.-O., Mizouri, A., Peach, A., & Testrow, C. P. (2023) · Physics Education · doi:10.1088/1361-6552/acc5cf · Cited by 199
Automated Essay Writing: An AIED Opinion
Sharples, M. (2022) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-022-00300-7 · Cited by 198
GPT Takes the Bar ExamPreprint
Bommarito, M., & Katz, D. (2022) · Social Science Research Network · doi:10.48550/arxiv.2212.14402 · Cited by 195
Bommarito, M. J., & Katz, D. M. (2022) · doi:10.2139/ssrn.4314839 · Cited by 181
Educational Research and AI-Generated Writing: Confronting the Coming Tsunami
Tate, T. P., Doroudi, S., Ritchie, D., Xu, Y., & uci, M. W. (2023) · doi:10.35542/osf.io/4mec3 · Cited by 137
Teaching for Critical Thinking
Brookfield, S. (2013) · International Journal of Adult Vocational Education and Technology · doi:10.4018/javet.2013010101 · Cited by 131
Kuleto, V., Ilić, M. P., Stănescu, M., Ranković, M., Šević, N. P., Păun, D. G., & Teodorescu, S. (2021) · Sustainability · doi:10.3390/su132111814 · Cited by 128
Assessing the quality of student-generated short answer questions using GPT-3
Moore, S., Nguyen, H. A., Bier, N., Domadia, T., & Stamper, J. (2022) · Lecture Notes in Computer Science · doi:10.1007/978-3-031-16290-9_18 · Cited by 93
Peng, H., Ma, S., & Spector, J. M. (2019) · Lecture notes in educational technology · doi:10.1007/978-981-13-6908-7_24 · Cited by 81
ChatGPT for (Finance) Research: The Bananarama ConjecturePreprint
Dowling, M., & Lucey, B. M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4322651 · Cited by 74
The moral authority of ChatGPTPreprint
Krügel, S., Ostermaier, A., & Uhl, M. (2023) · arXiv (Cornell University) · doi:10.48550/arxiv.2301.07098 · Cited by 54
Student Use of Automated Essay Evaluation Technology During Revision
Moore, N. S., & MacArthur, C. A. (2016) · Journal of Writing Research · doi:10.17239/jowr-2016.08.01.05 · Cited by 51
Towards Generalized Methods for Automatic Question Generation in Educational Domains
Nguyen, H. A., Bhat, S., Moore, S., Bier, N., & Stamper, J. C. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-16290-9_20 · Cited by 47
The Effect of Using Automated Essay Evaluation on ESL Undergraduate Students’ Writing Skill
Aluthman, E. S. (2016) · International Journal of English Linguistics · doi:10.5539/ijel.v6n5p54 · Cited by 45
MOOCs and upskilling in Australia: A qualitative literature study
Santandreu Calonge, D., Aman Shah, M., Riggs, K., Connor, M., & Wang, S. (2019) · Cogent Education · doi:10.1080/2331186x.2019.1687392 · Cited by 44
Teaching Machines: Learning from the Intersection of Education and Technology
Ferster, B. (2014) · Project Muse (Johns Hopkins University) · Cited by 42
Automatic argument assessment of final project reports of computer engineering students
García‐Gorrostieta, J. M., López‐López, A., & González‐López, S. (2018) · Computer Applications in Engineering Education · doi:10.1002/cae.21996 · Cited by 42
Anson, C. M., & Straume, I. S. (2022) · Journal of Academic Writing · doi:10.18552/joaw.v12i1.820 · Cited by 42
Hartmann, J., Schwenzow, J., & Witte, M. (2023) · arXiv · doi:10.48550/arxiv.2301.01768 · Cited by 37
The AI teacher test: Measuring the pedagogical ability of blender and GPT-3 in educational dialogues
Tack, A., & Piech, C. (2022) · arXiv · doi:10.48550/arxiv.2205.07540 · Cited by 36
A brief review of Mentimeter – a student response system
Rudolph, J. (2017) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2018.1.1.5 · Cited by 33
Self-citationBrookfield, S., Rudolph, J., & Yeo, E. (2019) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2019.2.2.11 · Cited by 30
Self-citationThe AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, A., & Piech, C. (2022) · Lirias (KU Leuven) · doi:10.5281/zenodo.6853187 · Cited by 30
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, A., & Piech, C. (2022) · Lirias (KU Leuven) · doi:10.5281/zenodo.6853186 · Cited by 30
Virtual Reality as a tool for learning: The past, present and the prospect
Akinola, Y. M., Agbonifo, O. C., & Sarumi, O. A. (2020) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2020.3.2.10 · Cited by 27
Rivas, M. J., Baker, R. B., & Evans, B. J. (2020) · AERA Open · doi:10.1177/2332858420973577 · Cited by 26
Artificial Intelligence in education: Rise of the Machines
Tan, S. (2020) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2020.3.1.17 · Cited by 25
Self-citationTechnology and education. Innovation and hindrances
(2022) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2022.5.s1 · Cited by 25
(2011) · The Electronic Journal of e-Learning · Cited by 24
Dark academia how universities die
Muttaqin, M. Z. (2021) · Journal of Higher Education Policy and Management · doi:10.1080/1360080x.2021.2014622 · Cited by 24
Tan, E. (2022) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2022.5.2.ss1 · Cited by 24
COmmunication’s ROugh NAvigations: ‘Fake’ news in a time of a global crisis
Kefalaki, M., & Karanicolas, S. (2020) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2020.3.1.19 · Cited by 16
Ma, H., & Slater, T. M. (2015) · Writing & Pedagogy · doi:10.1558/wap.v7i2-3.26376 · Cited by 15
Dark Academia. How Universities Die
Rudolph, J. (2021) · Journal of Education, Innovation, and Communication. · doi:10.34097/jeicom-3-1-june21-7 · Cited by 15
Self-citationFleming, P. J., Rudolph, J., & Tan, S. (2021) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2021.4.2.14 · Cited by 12
Self-citationArtificial intelligence is getting better at writing, and universities should worry about plagiarism
Mindzak, M., & Eaton, S. E. (2021) · doi:10.64628/aam.wwdgwwp3r · Cited by 12
Ji, Y., & Gao, S. (2023) · DROPS (Schloss Dagstuhl – Leibniz Center for Informatics) · doi:10.4230/lipics.giscience.2023.43 · Cited by 10
The war in Ukraine as an opportunity to teach critical thinking
Rudolph, J., & Tan, S. (2022) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2022.5.1.24 · Cited by 9
Self-citationThe History of Technology and Education
Terzian, S. G. (2019) · doi:10.1093/oxfordhb/9780199340033.013.33 · Cited by 8
ChatGPT Usage and LimitationsPreprint
Azaria, A. (2022) · HAL (Le Centre pour la Communication Scientifique Directe) · doi:10.13140/rg.2.2.26616.11526 · Cited by 8
New AI tools that can write student essays require educators to rethink teaching and assessment
Sharples, M. (2022) · London School of Economics and Political Science Research Online (London School of Economics and Political Science) · Cited by 8
The machines are learning: How artificial intelligence is already affecting journalism education
Sparrow, J. (2022) · The Australian Journalism Review · doi:10.1386/ajr_00101_7 · Cited by 5
Should we do away with exams altogether? No, but we need to rethink their design and purpose
Bergen, P. V., & Lane, R. (2016) · doi:10.64628/aa.g9ecmcg4k · Cited by 4
Editorial 5(SI1): Technology and education: Innovation or hindrance?
Kefalaki, M., Diamantidaki, F., & Rudolph, J. (2022) · Journal of Applied Learning & Teaching · doi:10.37074/jalt.2022.5.s1.1 · Cited by 4
Self-citationThe Oxford Handbook of The History of Education
Başoğlu, T. (2023) · İslâm Araştırmaları Dergisi · doi:10.26570/isad.1235854 · Cited by 1
Research works printed but not linked: 16
- [11]11. Aydın (Ed.), Emerging computer technologies 2 (pp. 22-31). İzmir Akademi Dernegi.
- [15]15. Bender, E. M., 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).
- [30]30. Cotton, D. R., Cotton, P. A., & Shipway, J. R. (2023, January 10). Chatting and cheating. Ensuring academic integrity in the era of ChatGPT. Preprint. https://doi.org/10.35542/osf. io/mrz8h D'Agostino, S. (2022, October 26). Machines can craft essays. How should writing be taught now? Inside Higher Ed, https:// www.insidehighered.com/news/2022/10/26/machines-can- craft-essays-how-should-writing-be-taught-now · DOI
- [45]45. Gilson, A., Safranek, C., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2022). How well does ChatGPT do when taking the medical licensing exams? The Implications of large language models for medical education and knowledge assessment. Preprint. medRxiv.
- [59]59. Heyward, E. (2022, May 16). Using AI to write essays isn't cheating, student says. Canta, (5), pp. 6-7. https://www. canta.co.nz/newsarticle/115524?newsfeedId=1453013
- [60]60. hooks, b. (2010). Teaching critical thinking. Routledge.
- [61]61. Huh, S. (2023). Are ChatGPT's knowledge and interpretation ability comparable to those of medical students in Korea for taking a parasitology examination?: A descriptive study. Journal of Educational Evaluation for Health Professions, 20(1), https://doi.org/10.3352/jeehp.2023 · DOI
- [62]62. Jiao, W., Wang, W., Huang, J., Wang, X., & Tu, Z. (2023, January 3). Is ChatGPT a good translator? A preliminary study. Preprint. https://wxjiao.github.io/downloads/tech_ chatgpt_arxiv.pdf
- [77]77. Kurzweil, R. (2005). The singularity is near. Viking Penguin.
- [79]79. Lim, V. F. (2022, December 16). ChatGPT raises uncomfortable questions about teaching and classroom learning. The Straits Times, https://www.straitstimes.com/opinion/need- to-review-literacy-assessment-in-the-age-of-chatgpt Liquid Ocelot (2023, January 2). ChatGPT-4, the newest and most advanced AI system, might prompt a major shift in the way we communicate. Medium, https://medium.com/ inkwater-atlas/chatgpt-4-the-newest-and-most-advanced- ai-system-might-prompt-a-major-shift-in-the-way-we- fd764f97212c
- [103]103. Nisar, S., & Aslam, M. S. (2023, January 14). Is ChatGPT a good tool for T&CM students in studying pharmacology? Preprint. https://ssrn.com/abstract=4324310
- [105]105. O'Connor, S. & ChatGPT (2023). Open artificial intelligence platforms in nursing education: tools for academic progress or abuse? Nurse Education in Practice, 66, 103537. https:// doi.org/10.1016/j.nepr.2022.1 · DOI
- [109]109. Parker, M., Rudolph, J., Shukaitis, S., & Tan, S. (2021). Strategic utopianism and the avoidance of dualisms: An interview with Martin Parker. Journal of Applied Learning and Teaching, 4(Sp. Iss. 1), 60-73. https://doi.org/10.37074/jalt.2021.4.s1. · DOI
- [115]115. Radford, A., Narasimhan, K., Salimans, T., & Sutskever, I. (2018). Improving language understanding by generative pre- training. Preprint. https://cdn.openai.com/research-covers/ language-unsupervised/language_understanding_paper. pdf
- [120]120. M.Ed. dissertation, University of Adelaide].
- [162]162. Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence
Cited by
Sorted by citations
Ray, P. P. (2023) · Internet of Things and Cyber-Physical Systems · doi:10.1016/j.iotcps.2023.04.003 · Cited by 2,463
What Is the Impact of ChatGPT on Education? A Rapid Review of the Literature
Lo, C. K. (2023) · Education Sciences · doi:10.3390/educsci13040410 · Cited by 2,024
BAİDOO-ANU, D., & OWUSU ANSAH, L. (2023) · Journal of AI · doi:10.61969/jai.1337500 · Cited by 3,939
A SWOT analysis of ChatGPT: Implications for educational practice and research
Farrokhnia, M., Banihashem, S. K., Noroozi, O., & Wals, A. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2195846 · Cited by 1,384
“Moreover, the ongoing increase of its training data helps ChatGPT to constantly be improved and updated with new data, which means it can become even more accurate over time (Rudolph et al., 2023).”
BackgroundInfluentialBaidoo-Anu, D., & Owusu Ansah, L. (2023) · doi:10.2139/ssrn.4337484 · Cited by 3,004
“Moreover, with Microsoft trying to incorporate ChatGPT holistically into its products (Rudolph et al., 2023; Warren, 2023), in no time ChatGPT will be conventional, and it may possibly be too late for educational institutions to rethink their policies and practices to guide and support their…”
Method
Metadata
- Authors
- Rudolph, J., Tan, S., & Tan, S.
- Venue
- Journal of Applied Learning & Teaching
- Publisher
- Open Access Publishing Association
- Published
- 2023-01-25
- Volume
- 6
- Issue
- 1
- ISSN
- 2591-801X (ISSN-L)
- OpenAlex
- W4317910584
- Semantic Scholar
- 9460f9fbc532416c8ec39591577032a5fa4a79b3
- Cited by
- 1,806
- References
- 84
- Citations by year
- 2026: 258 · 2025: 481 · 2024: 648 · 2023: 418
- FWCI
- 424.07
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Licence
- other-oa
- Locations
- Journal of Applied Learning & Teaching (publishedVersion, other-oa)
- Topics
- Social Sciences › Education › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Social Sciences › Education › Academic integrity and plagiarism
- Keywords
- ChatGPT, generative AI, student assessment, higher education, AI chatbots, artificial intelligence in education, OpenAI, future of teaching and learning, academic integrity
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review