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August 19, 20252 citationsOpen Access

Human-AI Learning: Architecture of a Human-agenticAI Learning System

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PWPeter WilliamsUniversity of Idaho

Key Points

  • Adaptive learning outcomes are achieved through collaboration between learners and AI agents, enhancing educational experiences.
  • The architecture tracks formative assessments of learners, leading to summative achievement portfolios for evaluating progress.
  • Observational analysis reviews existing AI learning models revealed significant gaps in supporting co-created learning in universities.
  • Incorporating 21st century skills, the model shows potential for diverse educational environments beyond higher education.

Abstract

The Ancient Greeks foresaw non-human automata and the power of dialogic learning, but Generative AI and Agentic AI afford the prospect of going beyond interlocutor to co-creator, in an empowering partnership between learner and AI agent to address ‘whole person’ education. This exploratory study reviews existing conceptual models and implementations of learning with AI before proposing the novel and original architecture of a human-agenticAI learning system. In this, the learner and human tutor are each supported by AI assistants, and an AI tutor coordinates the generation, presentation and assessment of adaptive learning activities requiring the partnership of learner and AI assistant in the co-creation of learning outcomes. The proposed model is significant for incorporating 21st Century skills in a diversity of realistic learning environments. It tracks a formative assessment pathway of the learner’s contribution to co-created outcomes, through to the compilation of a summative achievement portfolio for external warranting. Although focused upon learning in universities, the model is transferable to other educational milieux.

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Cite This Study

Peter Williams (2025) studied this question.

synapsesocial.com/papers/68af4eb4ad7bf08b1ead75b0https://doi.org/10.20944/preprints202508.1351.v1
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