The Chatbots’ Challenge to Education: Disruption or Destruction?
Open accessAbstract
The article addresses the positive and negative implications of the growing spread of chatbots based on large language models (LLMs) on instruction, learning, and assessment in education. It is based on extensive conversations with ChatGPT regarding pedagogy-related issues and relevant documents. Discussed are the challenges of chatbots like ChatGPT to educators—on the one hand, their potential to advance deep learning and the roles of the instructor and the school context in causing it to happen. On the other hand, it underscores the pedagogical drawbacks of improper usage of such chatbots and the instructional practices and school contexts that could escalate learning. Three school-culture components, namely classroom learning, teacher professional learning, and school leadership, are the essential aspects of pedagogical approaches that, in a particular constellation, could enhance and, in another, impede a chatbot’s potential to advance deep learning. The underlying theoretical framework is assessment-driven, contrasting assessment for learning (AfL) and assessment for grading, distinguishing assessment cultures from testing cultures. Patterns of chatbot usage that align with the principles of each culture are discussed. A sample of quotes from the conversations with ChatGPT is presented to support the insights gained from the chatting experience and the conclusions drawn.
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ChatGPT lacks emotional intelligence, limiting its ability to provide the kind of humanized interaction needed to establish emotional resonance with students or spark deeper learning interest.
“This may be because, although ChatGPT can quickly provide knowledge, answer questions, and generate content to enhance students' academic performance, it lacks emotional intelligence (Birenbaum, 2023), limiting its ability to provide the kind of”
From RETRACTED ARTICLE: The effect of ChatGPT on students’ learning performance, learning perception, and higher-order thinking: insights from a meta-analysis (2025) · cites this paper as Birenbaum, 2023
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Three Approaches to Qualitative Content Analysis
Hsieh, H.-F., & Shannon, S. E. (2005) · Qualitative Health Research · doi:10.1177/1049732305276687 · Cited by 44,601 · see citing works
A Coefficient of Agreement for Nominal Scales
Cohen, J. (1960) · Educational and Psychological Measurement · doi:10.1177/001316446002000104 · Cited by 42,398 · see citing works
Assessment and Classroom Learning
Black, P., & Wiliam, D. (1998) · Assessment in Education: Principles, Policy & Practice · doi:10.1080/0969595980050102 · Cited by 8,152 · see citing works
An Attributional Theory of Motivation and Emotion
Weiner, B. L. (1986) · Springer eBooks · doi:10.1007/978-1-4612-4948-1 · Cited by 4,964 · see citing works
Vescio, V. A., Ross, D. D., & Adams, A. (2007) · Teaching and Teacher Education · doi:10.1016/j.tate.2007.01.004 · Cited by 2,459 · see citing works
Conceptualizing Teacher Professional Learning
Opfer, V. D., & Pedder, D. (2011) · Review of Educational Research · doi:10.3102/0034654311413609 · Cited by 1,814 · see citing works
Conversational agents in healthcare: a systematic review
Laranjo, L., Dunn, A. G., Tong, H. L., Kocaballi, A. B., Chen, J., Bashir, R., Surian, D., Gallego, B., Magrabi, F., Lau, A. Y. S., et al. (2018) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocy072 · Cited by 1,388 · see citing works
What is assessment for learning
Wiliam, D. (2011) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2011.03.001 · Cited by 1,282 · see citing works
Complexity, Accountability, and School Improvement
O’Day, J. (2002) · Harvard Educational Review · doi:10.17763/haer.72.3.021q742t8182h238 · Cited by 510 · see citing works
All Systems Go: The Change Imperative for Whole System Reform
Fullan, M. J. (2010) · Corwin Press eBooks · doi:10.4135/9781452219554 · Cited by 449 · see citing works
Visible Learning: The Sequel: A Synthesis of Over 2,100 Meta-Analyses Relating to Achievement
Hattie, J. (2023) · doi:10.4324/9781003380542 · Cited by 443 · see citing works
Professional Capital as Accountability
Fullan, M. J., Rincón-Gallardo, S., & Hargreaves, A. (2015) · Education Policy Analysis Archives · doi:10.14507/epaa.v23.1998 · Cited by 240 · see citing works
Exploring the impact of chatbots on consumer sentiment and expectations in retail
Tran, A. D., Pallant, J. I., & Johnson, L. W. (2021) · Journal of Retailing and Consumer Services · doi:10.1016/j.jretconser.2021.102718 · Cited by 168 · see citing works
On the Origin of Hallucinations in Conversational Models: Is it the Datasets or the Models?
Dziri, N., Milton, S., Yu, M., Zaiane, O., & Reddy, S. (2022) · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies · doi:10.18653/v1/2022.naacl-main.387 · Cited by 121 · see citing works
Assessment for Learning: Meeting the Challenge of Implementation
Laveault, D., Allal, L., & Publishing, S. I. (2016) · The enabling power of assessment · doi:10.1007/978-3-319-39211-0 · Cited by 105 · see citing works
Butler, D. L., Schnellert, L., & MacNeil, K. A. (2014) · Journal of Educational Change · doi:10.1007/s10833-014-9227-z · Cited by 102 · see citing works
Improving Learning How to Learn
James, M., McCormick, R., Black, P., Carmichael, P., Drummond, M.-J., Fox, A., MacBeath, J., Marshall, B., Pedder, D., Procter, R., et al. (2007) · Routledge eBooks · doi:10.4324/9780203934319 · Cited by 92 · see citing works
Chatbots on the Rise: A New Narrative in Journalism
Veglis, A. A., & Maniou, T. A. (2019) · Studies in Media and Communication · doi:10.11114/smc.v7i1.3986 · Cited by 70 · see citing works
Birenbaum, M., Kimron, H., & Shilton, H. (2011) · Studies in Educational Evaluation · doi:10.1016/j.stueduc.2011.04.001 · Cited by 66 · see citing works
Self-citationUsing Computers to Assess New Educational Goals
Ridgway, J., & McCusker, S. (2003) · Assessment in Education Principles Policy and Practice · doi:10.1080/0969594032000148163 · Cited by 50 · see citing works
Organizing Schools for Productive Learning
Sharan, S., & Tan, I. G. C. (2008) · Springer eBooks · doi:10.1007/978-1-4020-8395-2 · Cited by 47 · see citing works
Integrating Multi-User Virtual Environments in Modern Classrooms
Qian, Y. 1. (2017) · Advances in educational technologies and instructional design book series · doi:10.4018/978-1-5225-3719-9 · Cited by 17 · see citing works
Assessment Understood as Enabling
Wyatt‐Smith, C., Klenowski, V., & Colbert, P. (2014) · The enabling power of assessment · doi:10.1007/978-94-007-5902-2_1 · Cited by 15 · see citing works
Flagged first, then by citations
Research works printed but not linked: 13
- Okuda, T.; Shoda, S. Ai-based chatbot service for financial industry. FUJITSU Sci. Technol. J. 2018, 54, 4-8. Available online: https://www.fujitsu.com/global/documents/about/resources/publications/fstj/archives/vol54-2/paper01.pdf (accessed on 1 March 2023).
- Teoli, D.; Sanvictores, T.; An, J. SWOT Analysis; StatPearls: Treasure Island, FL, USA, 2022; Available online: https://europepmc. org/article/med/30725987 (accessed on 12 November 2022).
- Ji, Z.; Lee, N.; Frieske, R.; Yu, T.; Su, D.; Xu, Y.; Ishii, E.; Bang, Y.; Dai, W.; Madotto, A.; et al. Survey of Hallucination in Natural Language Generation. ACM Computing Surveys. Assoc. Comput. Mach. 2022, 55, 1-38. [CrossRef] · DOI · Paper page
- Qian, Y., Ed.; IGI Global: Hershey, PA, USA, 2018; pp. 240-258. [CrossRef] · DOI
- Hattie, J. Visible Learning: A Synthesis of Over 800 Meta-Analyses Relating to Achievement; Routledge: New York, NY, USA; Abingdon, UK, 2009.
- Nichols, S.L.; Berliner, D.C. Collateral Damage: How High-Stakes Testing Corrupts American Schools; Harvard Education Press: Cambridge, MA, USA, 2007.
- Birenbaum, M. Conceptualizing assessment culture in school. In Designing Assessment for Quality Learning. The Enabling Power of Assessment Vol. 1; Wyatt-Smith, C., Klenowski, V., Colbert, P., Eds.; Springer: Dordrecht, The Netherlands, 2014; pp. 285-302.
- Mitleton-Kelly, E. Ten principles of complexity and enabling infrastructures. In Complex Systems and Evolutionary Perspectives of Organizations: The Application of Complexity Theory to Organizations; Mitleton-Kelly, E., Ed.; Elsevier: Oxford, UK, 2003; pp. 23-50.
- ARG (Assessment Reform Group). Assessment for Learning: 10 Principles; University of Cambridge School of Education: Cambridge, UK, 2002.
- McLaughlin, M.W.; Talbert, J.E. Building School-Based Teacher Learning Communities: Professional Strategies to Improve Student Achievement; Teachers College Press: New York, NY, USA, 2006.
- Sarason, S.B. How Schools Might Be Governed and Why; Teachers College Press: New York, NY, USA, 1997.
- OECD. Skills for Social Progress: The Power of Social and Emotional Skills; OECD Skills Studies; OECD Publishing: Paris, France, 2015. [CrossRef] · DOI
- Tishman, S.; Perkins, D.N.; Jay, E. The Thinking Classroom: Learning and Teaching in a Culture of Thinking; Pearson: Boston, MA, USA, 1994; ISBN 100205165087.
Cited by
Sorted by citations
Wang, J., & Fan, W. (2025) · Humanities and Social Sciences Communications · doi:10.1057/s41599-025-04787-y · Cited by 322 · see citing works
RetractedChoudhury, A., & Chaudhry, Z. (2024) · Journal of Medical Internet Research · doi:10.2196/56764 · Cited by 159 · see citing works
Biri, S. K., Kumar, S., Panigrahi, M., Mondal, S., Behera, J. K., & Mondal, H. (2023) · Cureus · doi:10.7759/cureus.47468 · Cited by 40 · see citing works
- Authors
- Birenbaum, M.
- Affiliations
- Tel Aviv University (IL)
- Corresponding author
- Birenbaum, Menucha
- ORCID
- Birenbaum, Menucha
- Venue
- Education Sciences
- Publisher
- MDPI AG
- Published
- 2023-07-13
- Volume
- 13
- Issue
- 7
- Pages
- 711
- ISSN
- 2227-7102 (ISSN-L)
- OpenAlex
- W4384340967
- Cited by
- 61
- References
- 23
- Citations by year
- 2026: 14 · 2025: 19 · 2024: 24 · 2023: 4
- FWCI
- 14.32
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Education Sciences (publishedVersion, cc-by)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- 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 › Information Systems › Digital Education and Society
- Keywords
- chatbots, large language models, ChatGPT, deep learning, assessment for learning, evaluation culture, testing culture, teacher learning, school leadership, classroom learning, instructional practices, educational disruption, artificial intelligence in education
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