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From Large Language Models to Human-Centred Learning: Rethinking Learner Agency in Education 5.0

  • Shruti DwivediSenior Research Scholar, Department of Education, University of Lucknow
  • Prof. Tripta TrivediProfessor, Department of Education, University of Lucknow

Keywords:

Education 5.0; large language models; learner agency; generative artificial intelligence; human-centred learning; Self-Determination Theory; Cognitive Load Theory; Human-Centred Artificial Intelligence

Abstract

Education 5.0 is about the usage of advanced technologies to help people grow, learn in ways that suit them, stay well connected and take part responsibly. In other words it incorporates personalisation and adaptation according to the needs of the learner. Now there are Large language models (LLMs) which can explain topics, give feedback, which can have a conversation and respond to individual learner needs. But these same capabilities may also cause cognitive offloading, over-reliance on automated responses, less reflection, and feeling less ownership of learning. This leads to the main question of this paper which is to understand under what pedagogical conditions can learning with help of LLMs make learners stronger and more independent or make them weaker.
This paper presents integrative conceptual review as it brings five existing ideas which are Self-Determination Theory (motivation), Cognitive Load Theory (mental effort), the Zone of Proximal Development (the right level of help), Human-Centred Artificial Intelligence (people stay in control) and research on cognitive engagement ( cognitive engagement). This paper argues that the educational impact of LLMs is not determined by technology alone but the LLM affordances does not act on the student directly but the lesson design of the lesson decides how they are used. Learner agency is not one skill but it is conceptualized as a multi-dimensional skill involving making real choices, taking an active part, self-regulation, evaluative judgment and taking responsibility for learning. An integrative mediation architecture is proposed where the pedagogical design conditions influence learners' psychological needs, satisfaction, productive cognitive engagement and calibrated boundary conditions are considered prior knowledge, task type, AI literacy, and learning context. In this paper five propositions are developed on learner choices, calibrated scaffolding, productive cognitive engagement, transparency and human control, and pedagogical alignment. The paper builds a mechanism-oriented view, showing how identical LLM capabilities may lead to different agency outcomes under different pedagogical conditions, and it provides a basis for future research.

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How to cite

Shruti Dwivedi, Prof. Tripta Trivedi (2026). From Large Language Models to Human-Centred Learning: Rethinking Learner Agency in Education 5.0. International Journal for Research in Education, 15(11), 1-9. https://doi.org/10.63345/ijre.v15.i11.IJRE1126001

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This article is open access, published under the CC BY 4.0 licence. Copyright remains with the authors.