BJET Editorial 2024: A call for research rigour
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Current empirical evidence regarding short- and long-term impacts of GenAI on learning outcomes is limited.
“Despite the promising design of systems like Khanmigo and students' positive attitudes towards using such technologies for personalised learning support [17], it is important to acknowledge the current limitations in empirical evidence regarding their short-and long-term impacts on learning outcomes [18].”
From Promises and challenges of generative artificial intelligence for human learning (2024) · cites this paper as [18]
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Promises and challenges of generative artificial intelligence for human learning
Yan, L., Greiff, S., Teuber, Z., & Gašević, D. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-02004-5 · Cited by 499 · see citing works
“To address these challenges, it is essential to establish standards for appraising the quality of evidence on GenAI’s effect on learning processes, outcomes and experiences 18 .”
Beyond the “Wow” Factor: Using Generative AI for Increasing Generative Sense-Making
Makransky, G., Shiwalia, B. M., Herlau, T., & Blurton, S. (2025) · Educational Psychology Review · doi:10.1007/s10648-025-10039-x · Cited by 27 · see citing works
- Authors
- Hennessy, S., Cukurova, M., Lewin, C., Mavrikis, M., & Major, L.
- Affiliations
- University of Cambridge (GB)
- University College London (GB)
- Manchester Metropolitan University (GB)
- University of Manchester (GB)
- Venue
- British Journal of Educational Technology
- Publisher
- Wiley
- Published
- 2023-12-28
- Volume
- 55
- Issue
- 1
- Pages
- 5-9
- ISSN
- 0007-1013 (ISSN-L)
- 1467-8535
- OpenAlex
- W4390346382
- Cited by
- 17
- References
- 0
- Citations by year
- 2026: 7 · 2025: 9 · 2024: 1
- FWCI
- 12.60
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- British Journal of Educational Technology (publishedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- Topics
- Social Sciences › Education › Educational Research and Methods
- Social Sciences › Arts and Humanities › History and Philosophy of Science › Publishing and Scholarly Communication
- Physical Sciences › Computer Science › Information Systems › Educational Technology in Learning
- Keywords
- scientific rigor, research methodology, educational technology research, research quality
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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.
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