Who Is Thinking?
Cognitive Delegation, Learning Missions, and the Teacher’s Role in the Age of Generative Artificial Intelligence
DOI:
https://doi.org/10.59471/raia2026238Keywords:
didactics, problem-based learning, project-based learning, competencies, generative artificial intelligence, cognitive delegation, learning missions, cognitive density, scaffolding, teacher agencyAbstract
The rise of generative artificial intelligence forces a revision of assumptions that have become entrenched in contemporary pedagogical discourse: that activity by itself produces learning, that projects automatically develop critical thinking, that student autonomy requires reducing teacher intervention, and that competency development can be conceived separately from knowledge construction. This article argues that none of these four assumptions withstands close scrutiny against the available evidence on problem-based learning, project-based learning, cognitive load, and scaffolding, and proposes shifting the discussion away from the choice of active methodologies toward the design of learning missions, understood as intentional architectures of cognitive experience that articulate problems, knowledge, cognitive operations, interactions, mediations, teacher interventions, technologies, and evidence. The central argument concerns the risk of cognitive delegation, that is, the displacement of specific intellectual operations onto external resources, particularly artificial intelligence systems. Delegation is not intrinsically negative; the problem arises when the operation delegated is precisely the one that constitutes the object of learning, and artificial intelligence does not by itself create educational superficiality but rather makes visible, and can amplify, a superficiality that certain pedagogical designs already contained. The article brings together classic contributions on problem-based learning, cognitive load, scaffolding, and cognitive apprenticeship with recent research on generative artificial intelligence, critical thinking, cognitive dependence, and the evaluation of student-AI interactions, and introduces the categories of cognitive density and delegation architecture as didactic design tools. It concludes by proposing that teachers be restored to the role of designers of the cognitive architecture of the experience, responsible for defining what can be delegated, what must be verified, and what operations must necessarily remain in the student’s hands.
Downloads
References
Barrows, H. S. (1986). A taxonomy of problem-based learning methods. Medical Education, 20(6), 481–486. https://doi.org/10.1111/j.1365-2923.1986.tb01386.x
Becerra, G., Losada, M., & Medina Zuta, P. (2025). Delegación cognitiva e Inteligencia Artificial. Repositorio UFLO.
Chi, M. T. H., & Wylie, R. (2014). The ICAP framework: Linking cognitive engagement to active learning outcomes. Educational Psychologist, 49(4), 219–243. https://doi.org/10.1080/00461520.2014.965823
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the crafts of reading, writing, and mathematics. En L. B. Resnick (Ed.), Knowing, learning, and instruction: Essays in honor of Robert Glaser (pp. 453–494). Lawrence Erlbaum Associates.
Craik, F. I. M., & Lockhart, R. S. (1972). Levels of processing: A framework for memory research. Journal of Verbal Learning and Verbal Behavior, 11(6), 671–684. https://doi.org/10.1016/S0022-5371(72)80001-X
Frøsig, T. B., & Romero, M. (2024). Teacher agency in the age of generative AI: Towards a framework of hybrid intelligence for learning design. arXiv. https://doi.org/10.48550/arXiv.2407.06655
Hmelo-Silver, C. E. (2004). Problem-based learning: What and how do students learn? Educational Psychology Review, 16(3), 235–266.
Li, L., Yu, F., & Zhang, E. (2024). A systematic review of learning task design for K-12 AI education: Trends, challenges, and opportunities. Computers and Education: Artificial Intelligence, 6, 100217. https://doi.org/10.1016/j.caeai.2024.100217
Loyens, S. M. M., van Meerten, J. E., Schaap, L., & Wijnia, L. (2023). Situating higher-order, critical, and critical-analytic thinking in problem- and project-based learning environments: A systematic review. Educational Psychology Review, 35, 39. https://doi.org/10.1007/s10648-023-09757-x
Oliveira, M. J. B., Zednik, C., Bombaerts, G., Sadowski, B., & Conijn, R. (2025). Assessing students’ DRIVE: A framework to evaluate learning through interactions with generative AI. Computers and Education: Artificial Intelligence, 9, 100497. https://doi.org/10.1016/j.caeai.2025.100497
Suriano, R., Plebe, A., Acciai, A., & Fabio, R. A. (2025). Student interaction with ChatGPT can promote complex critical thinking skills. Learning and Instruction, 95, 102011. https://doi.org/10.1016/j.learninstruc.2024.102011
Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4
Sweller, J., van Merriënboer, J. J. G., & Paas, F. G. W. C. (1998). Cognitive architecture and instructional design. Educational Psychology Review, 10(3), 251–296. https://doi.org/10.1023/A:1022193728205
Thomas, J. W. (2000). A review of the research on project-based learning. The Autodesk Foundation.
Tian, J., & Zhang, R. (2025). Learners’ AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy. Acta Psychologica, 260, 105725. https://doi.org/10.1016/j.actpsy.2025.105725
UNESCO. (2024). AI competency framework for teachers. UNESCO.
Wang, K. D., Wu, Z., Tufts II, L., Wieman, C., Salehi, S., & Haber, N. (2024). Scaffold or crutch? Examining college students’ use and views of generative AI tools for STEM education. arXiv. https://doi.org/10.48550/arXiv.2412.02653
Wood, D., Bruner, J. S., & Ross, G. (1976). The role of tutoring in problem solving. Journal of Child Psychology and Psychiatry, 17(2), 89–100. https://doi.org/10.1111/j.1469-7610.1976.tb00381.x
Downloads
Published
Issue
Section
License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
