Learning with ChatGPT 3.5 as a more knowledgeable other: an autoethnographic study
Open accessAbstract
ChatGPT, an artificial intelligence language model introduced in November 2022, is potentially applicable in many contexts, including higher education. Although academics are already using it to draft papers or develop search queries for systematic reviews, its use as a tool aiding the learning process has not been examined. To address this research gap, I conducted an autoethnographic study examining my experience using ChatGPT as a more knowledgeable other that scaffolded my learning about a particular topic—the technical aspects of how ChatGPT works. Overall, ChatGPT provided me with enough content to form a general idea of its technical aspects, and I experienced its feedback as motivating and relevant. However, the answers were somewhat superficial, the text it generated was not always consistent or logical and sometimes contradictory. The instantaneous replies to my questions contributed to an experience of a 'flow'. Being 'in the zone' also meant I overestimated my knowledge and understanding, as I could not detect the contradictory responses it provided 'on the spot'. I conclude that caution is advised when ChatGPT is used as a learning aid, as we learn more about its capabilities and limitations and how humans tend to perceive and interact with these technologies.
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
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?
ChatGPT provides immediate feedback and a plethora of information, enhancing learning efficiency and allowing for personalized educational paths.
“It provides immediate feedback and a plethora of information, enhancing learning efficiency and allowing for personalized educational paths (Stojanov, 2023;Wu et al., 2023a).”
From Empowering ChatGPT with Guidance Mechanism in Blended Learning: Effect of Self-Regulated Learning, Higher-Order Thinking Skills, and Knowledge Construction (2024) · cites this paper as Stojanov, 2023
The first-person account reports instant answers, relevant feedback, and learning that the author felt was faster and more efficient (Results; “Is it 'safe' to use ChatGPT?”, page unavailable). It also describes following the author's own questions and interests, but does not establish that ChatGPT provides personalized educational paths generally; the study concerns one learner's experience. (LLM, conf=0.83)
Experimental — accuracy not yet measured
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483 · see citing works
(1978) · Medical Entomology and Zoology · Cited by 53,488 · see citing works
The case for motivated reasoning.
Kunda, Z. (1990) · Psychological Bulletin · doi:10.1037/0033-2909.108.3.480 · Cited by 9,022 · cited 2× · see citing works
“In other words, I am engaged in motivated reasoning (Kunda, 1990), perceiving ChatGPT as I want to perceive it (i.e. human-like), not as it is (elaborate software).”
BackgroundKruger, J., & Dunning, D. (1999) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.77.6.1121 · Cited by 7,731 · see citing works
Chatting and cheating: Ensuring academic integrity in the era of ChatGPT
Cotton, D. R. E., Cotton, P. A., & Shipway, J. R. (2024) · Innovations in Education and Teaching International · doi:10.1080/14703297.2023.2190148 · Cited by 3,087 · see citing works
Chatting and Cheating. Ensuring academic integrity in the era of ChatGPT
Cotton, D., Cotton, P., & Shipway, J. R. (2023) · doi:10.35542/osf.io/mrz8h · Cited by 3,079 · see citing works
SPERBER, D., CLÉMENT, F., HEINTZ, C., MASCARO, O., MERCIER, H., ORIGGI, G., & WILSON, D. (2010) · Mind & Language · doi:10.1111/j.1468-0017.2010.01394.x · Cited by 1,795 · see citing works
ChatGPT is fun, but not an author
Thorp, H. H. (2023) · Science · doi:10.1126/science.adg7879 · Cited by 1,437 · see citing works
Blut, M., Wang, C., Wünderlich, N. V., & Brock, C. (2021) · Journal of the Academy of Marketing Science · doi:10.1007/s11747-020-00762-y · Cited by 1,194 · see citing works
ChatGPT listed as author on research papers: many scientists disapprove
Stokel-Walker, C. (2023) · Nature · doi:10.1038/d41586-023-00107-z · Cited by 868 · see citing works
ChatGPT: the future of discharge summaries?
Patel, S. B., & Lam, K. (2023) · The Lancet Digital Health · doi:10.1016/s2589-7500(23)00021-3 · Cited by 728 · see citing works
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 611 · see citing works
Toward a Psychology of Optimal Experience
Csíkszentmihályi, M. (2014) · Springer eBooks · doi:10.1007/978-94-017-9088-8_14 · Cited by 426 · see citing works
Chatterjee, J., & Dethlefs, N. (2023) · Patterns · doi:10.1016/j.patter.2022.100676 · Cited by 263 · see citing works
Evaluating ChatGPT as an Adjunct for Radiologic Decision-Making
Rao, A., Kim, J., Kamineni, M., Pang, M., Lie, W., & Succi, M. D. (2023) · doi:10.1101/2023.02.02.23285399 · Cited by 257 · see citing works
Can ChatGPT draft a research article? An example of population-level vaccine effectiveness analysis
Macdonald, C., Adeloye, D., Sheikh, A., & Rudan, I. (2023) · Journal of Global Health · doi:10.7189/jogh.13.01003 · Cited by 243 · see citing works
Analogy, higher order thinking, and education
Richland, L. E., & Simms, N. K. (2015) · Wiley Interdisciplinary Reviews Cognitive Science · doi:10.1002/wcs.1336 · Cited by 219 · see citing works
Hartmann, J., Schwenzow, J., & Witte, M. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4316084 · Cited by 186 · see citing works
Enablers and constraints to the use of inquiry-based learning in undergraduate education
Spronken‐Smith, R., Walker, R., Batchelor, J., O’Steen, B., & Angelo, T. A. (2011) · Teaching in Higher Education · doi:10.1080/13562517.2010.507300 · Cited by 102 · see citing works
Feedback and self‐regulated learning: insights from supervisors’ and PhD examiners’ reports
Stracke, E., & Kumar, V. (2010) · Reflective Practice · doi:10.1080/14623940903525140 · Cited by 69 · see citing works
The Risks of Using ChatGPT to Obtain Common Safety-Related Information and AdvicePreprint
Oviedo-Trespalacios, Ó., Peden, A. E., Cole‐Hunter, T., et al. (2023) · SSRN Electronic Journal · doi:10.2139/ssrn.4346827 · Cited by 32 · see citing works
The hypercorrection effect in younger and older adults
Eich, T. S., Stern, Y., & Metcalfe, J. (2012) · Aging Neuropsychology and Cognition · doi:10.1080/13825585.2012.754399 · Cited by 22 · see citing works
Flagged first, then by citations
Research works printed but not linked: 4
- Jiao, W., Wang, W., Huang, J-T, Wang, X., & Tu, Z. (2023). Is ChatGPT A good translator? Yes With GPT-4 As The Engine. ArXiv. https:// arxiv. org/ abs/ 2301. 08745
- Vygotsky, L. S., Cole, M., John-Steiner, V., Scribner, S., & Souberman, E. (1978). Mind in society development of higher psycho- logical processes. Harvard University Press.
- Vygotsky, L. (1986). Thought and language. MIT Press.
- Wang S., Scells, H., Koopman, B., Zuccon, G. (2023). Can ChatGPT write a good Boolean query for systematic review litera- ture search? ArXiv. https:// arxiv. org/ abs/ 2302. 03495
Cited by
Sorted by citations
Bahroun, Z., Anane, C., Ahmed, V., & Zacca, A. (2023) · Sustainability · doi:10.3390/su151712983 · Cited by 784 · see citing works
Yusuf, A., Pervin, N., & Román-González, M. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00453-6 · Cited by 554 · see citing works
“Stojanov (2023) emphasizes GenAI’s role in revolutionizing teaching, specifically its capacity to customize education to individual needs.”
BackgroundAbbas, M., Jam, F. A., & Khan, T. I. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00444-7 · Cited by 531 · see citing works
“…AI technologies, ChatGPT (OpenAI, 2022) has gained widespread popularity in academic settings for a variety of uses such as generation of codes or text, assistance in research, and the completion of assignments, essays and academic projects (Bahroun et al., 2023; Stojanov, 2023; Str-zelecki, 2023).”
BackgroundDoes ChatGPT enhance student learning? A systematic review and meta-analysis of experimental studies
Deng, R., Jiang, M., Yu, X., Lu, Y., & Liu, S. (2025) · Computers & Education · doi:10.1016/j.compedu.2024.105224 · Cited by 531 · see citing works
Lee, H.-Y., Chen, P.-H., Wang, W.-S., Huang, Y.-M., & Wu, T.-T. (2024) · International Journal of Educational Technology in Higher Education · doi:10.1186/s41239-024-00447-4 · Cited by 273 · see citing works
“Its efficacy as a supplementary educational tool has been further underscored through self-assessment studies (Stojanov, 2023).”
BackgroundGenerative <scp>AI</scp> in education and research: A systematic mapping review
Yusuf, A., Pervin, N., Román‐González, M., & Noor, N. M. (2024) · Review of Education · doi:10.1002/rev3.3489 · Cited by 182 · see citing works
Akiba, D., & Fraboni, M. C. (2023) · Education Sciences · doi:10.3390/educsci13090885 · Cited by 115 · see citing works
Liu, Z.-M., Hwang, G.-J., Chen, C.-Q., Chen, X.-D., & Ye, X.-D. (2026) · Computer Assisted Language Learning · doi:10.1080/09588221.2024.2389923 · Cited by 115 · see citing works
Yusuf, A., Bello, S., Pervin, N., & Tukur, A. K. (2024) · Thinking Skills and Creativity · doi:10.1016/j.tsc.2024.101619 · Cited by 102 · see citing works
Jacobsen, L. J., & Weber, K. E. (2023) · doi:10.31219/osf.io/cr257 · Cited by 57 · see citing works
A Survey on Student Use of Generative AI Chatbots for Academic Research
Deschenes, A., & McMahon, M. (2024) · Evidence Based Library and Information Practice · doi:10.18438/eblip30512 · Cited by 49 · see citing works
Faisal, E. (2024) · Frontiers in Education · doi:10.3389/feduc.2024.1325601 · Cited by 44 · see citing works
“While most of these studies validate ChatGPT’s significance in enhancing student learning, Stojanov (2023) adopts a more cautious stance toward its utilization.”
ResultJin, F., Peng, X., Sun, L., Song, Z., Zhou, K., & Lin, C. (2025) · Journal of Computer Assisted Learning · doi:10.1111/jcal.70004 · Cited by 40 · see citing works
Liu, D., Fan, G., & Pan, L. (2026) · International Journal of STEM Education · doi:10.1186/s40594-025-00592-w · Cited by 16 · see citing works
- Authors
- Stojanov, A.
- Affiliations
- University of Otago (NZ)
- Corresponding author
- Stojanov, Ana
- ORCID
- Stojanov, Ana
- Venue
- International Journal of Educational Technology in Higher Education
- Published
- 2023-06-19
- Volume
- 20
- Issue
- 1
- ISSN
- 2365-9440 (ISSN-L)
- OpenAlex
- W4381149642
- Cited by
- 169
- References
- 23
- Citations by year
- 2026: 40 · 2025: 64 · 2024: 53 · 2023: 12
- FWCI
- 39.67
- Type
- journal article
- Language
- en
- Open access
- diamond
- doi.org
- Locations
- International Journal of Educational Technology in Higher Education (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Universitat Oberta de Catalunya
- Topics
- Physical Sciences › Computer Science › Information Systems › Artificial Intelligence in Education
- Health Sciences › Medicine › Health Informatics › Artificial Intelligence in Healthcare and Education
- Physical Sciences › Computer Science › Artificial Intelligence › Intelligent Tutoring Systems and Adaptive Learning
- Keywords
- ChatGPT, large language models, more knowledgeable other, scaffolding, AI-assisted learning, flow experience, overconfidence, higher education
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