Journal: Region - Educational Research and Reviews DOI: 10.32629/rerr.v8i5.5479
Abstract
Generative AI can supply an explanation before a learner has decided what evidence would make it credible. In scientific inquiry, AI-enabled assistance may improve an answer while removing responsibility for judging it. This paper proposes epistemic responsibility allocation as a guiding principle for educational multi-agent systems. A responsibility specifies what an actor must justify, what the actor is prohibited from doing, and when decision-making authority passes to a teacher. An Expert verifies approved sources, a Peer raises evidence-seeking challenges, and a Coach manages and withdraws instructional scaffolds. A ledger adapts Toulmin's structure to record claims, evidence, warrants, qualifiers, challenges, and student revisions. Four propositions alongside a proposed comparison against a single-agent interface make the framework empirically testable. Multiple agents deliver practical benefits only when permissions create genuinely distinct responsibilities among them.
Keywords
generative artificial intelligence; epistemic responsibility; scientific argumentation; multi-agent systems; learning design; teacher orchestration
Full Text
PDF - Viewed/Downloaded: 0 TimesReferences
[1] Hmelo-Silver C E, Duncan R G, Chinn C A. Scaffolding and achievement in problem-based and inquiry learning[J]. Educational Psychologist, 2007, 42(2): 99-107. https://doi.org/10.1080/00461520701263368
[2] Chi M T H, Wylie R. The ICAP framework: Linking cognitive engagement to active learning outcomes[J]. Educational Psychologist, 2014, 49(4): 219-243. https://doi.org/10.1080/00461520.2014.965823
[3] Toulmin S E. The uses of argument (Updated ed.)[M]. Cambridge: Cambridge University Press, 2003.
[4] Osborne J, Erduran S, Simon S. Enhancing the quality of argumentation in school science[J]. Journal of Research in Science Teaching, 2004, 41(10): 994-1020. https://doi.org/10.1002/tea.20035
[5] Chiu T K F. A classification tool to foster self-regulated learning with generative artificial intelligence by applying self-determination theory: A case of ChatGPT[J]. Educational Technology Research and Development, 2024, 72: 2401-2416. https://doi.org/10.1007/s11423-024-10366-w
[6] Lee H Y, Chen P H, Wang W S, et al. Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction[J]. International Journal of Educational Technology in Higher Education, 2024, 21: 16. https://doi.org/10.1186/s41239-024-00447-4
[7] Alfredo R, Echeverria V, Jin Y, et al. Human-centred learning analytics and AI in education: A systematic literature review[J]. Computers and Education: Artificial Intelligence, 2024, 6: 100215. https://doi.org/10.1016/j.caeai.2024.100215
[8] Miao F, Cukurova M. AI competency framework for teachers[R]. UNESCO, 2024.
https://www.unesco.org/en/articles/ai-competency-framework-teachers
[9] The Design-Based Research Collective. Design-based research: An emerging paradigm for educational inquiry[J]. Educational Researcher, 2003, 32(1): 5-8. https://doi.org/10.3102/0013189X032001005
[2] Chi M T H, Wylie R. The ICAP framework: Linking cognitive engagement to active learning outcomes[J]. Educational Psychologist, 2014, 49(4): 219-243. https://doi.org/10.1080/00461520.2014.965823
[3] Toulmin S E. The uses of argument (Updated ed.)[M]. Cambridge: Cambridge University Press, 2003.
[4] Osborne J, Erduran S, Simon S. Enhancing the quality of argumentation in school science[J]. Journal of Research in Science Teaching, 2004, 41(10): 994-1020. https://doi.org/10.1002/tea.20035
[5] Chiu T K F. A classification tool to foster self-regulated learning with generative artificial intelligence by applying self-determination theory: A case of ChatGPT[J]. Educational Technology Research and Development, 2024, 72: 2401-2416. https://doi.org/10.1007/s11423-024-10366-w
[6] Lee H Y, Chen P H, Wang W S, et al. Empowering ChatGPT with guidance mechanism in blended learning: Effect of self-regulated learning, higher-order thinking skills, and knowledge construction[J]. International Journal of Educational Technology in Higher Education, 2024, 21: 16. https://doi.org/10.1186/s41239-024-00447-4
[7] Alfredo R, Echeverria V, Jin Y, et al. Human-centred learning analytics and AI in education: A systematic literature review[J]. Computers and Education: Artificial Intelligence, 2024, 6: 100215. https://doi.org/10.1016/j.caeai.2024.100215
[8] Miao F, Cukurova M. AI competency framework for teachers[R]. UNESCO, 2024.
https://www.unesco.org/en/articles/ai-competency-framework-teachers
[9] The Design-Based Research Collective. Design-based research: An emerging paradigm for educational inquiry[J]. Educational Researcher, 2003, 32(1): 5-8. https://doi.org/10.3102/0013189X032001005
Copyright © 2026 Ziyun ZHANG
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License