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Artificial intelligence as a cognitive partner: a developmental framework for human-AI co-regulation in learning

● high · 2026-08-16 · learning-theory, self-regulated-learning, metacognition, cognitive-offloading, scaffolding, distributed-cognition, developmental-psychology, higher-ed

Synthesis: This conceptual analysis by S, Joseph, Jose, S. M, N, & Joseph (2026) proposes that AI should be understood not merely as an external tool but as a cognitive partner in the co-regulation of thinking, learning, and self-control. Drawing on executive function, Metacognition, distributed cognition, and sociocultural development, it frames human-AI interaction as co-regulated cognition where AI acts as a scaffold, metacognitive support, external memory system, and decision partner. The framework is argued to be most relevant in middle childhood, adolescence, and adulthood, weighing the benefits of cognitive offloading against the risks of over-reliance.

Artificial intelligence as a cognitive partner

The shift from tool to cognitive partner

The paper argues that developmental psychology has lacked a theoretical framework for the role of AI in cognition regulation across the lifespan. It proposes that AI participates in the co-regulation of thought and action rather than merely providing information. Grounded in learning theory, the authors integrate executive function, Metacognition, distributed cognition, and sociocultural (Vygotskian) development to describe a developmental paradigm of human-AI co-regulation.

Four roles of AI in cognitive regulation

  1. Scaffold for cognitive performance — AI systems (e.g., intelligent tutoring systems) enable learners to work beyond their independent capability, offering 24-hour support, real-time Feedback, and dynamically adjusted difficulty, extending traditional Scaffolding.
  2. Metacognitive support — conversational AI prompts users to rethink answers, generate alternative explanations, and validate their reasoning, supporting self-regulated learning.
  3. External memory and cognitive offloading system — AI stores, retrieves, and generates information, offloading working-memory load in line with Cognitive Offloading research.
  4. Decision partner — recommendation and conversational systems participate in planning and decision-making, framing AI as a collaborator rather than a tool.

Developmental stages and co-regulation

The framework is stage-sensitive: it is most directly applicable to middle childhood, adolescence, and adulthood, where metacognitive and self-regulatory capacities are developed enough for meaningful human-AI collaboration. In early childhood, AI's role is limited to structured external regulation of behavior. Across later stages, AI shifts from metacognitive partner (middle childhood and adolescence) to collaborator in complex cognition (adulthood).

Benefits and risks

AI-assisted co-regulation can improve performance, reduce cognitive load, and extend memory through beneficial offloading. However, the authors warn of the risks of excessive Cognitive Offloading, Over-Reliance on external advice, and reduced effortful processing and independent reasoning — outcomes that can undermine the development of self-regulation and Critical Thinking skills, especially in younger learners.

Key Findings

  • Proposes a developmental framework of human-AI co-regulation in which AI is conceptualized not merely as an external tool but as a cognitive partner in the co-regulation of thinking, learning, and self-control.
  • Integrates executive function, metacognition, distributed cognition, and sociocultural development theories to frame AI-mediated cognition as co-regulated between learner and intelligent system.
  • Identifies four roles for AI in cognitive regulation: scaffold, metacognitive support, external memory / cognitive offloading system, and decision partner.
  • Argues the framework is most relevant in middle childhood, adolescence, and adulthood; early childhood AI support is limited to structured external regulation.
  • Highlights both benefits (performance gains via offloading, scaffolding, reduced cognitive load) and risks (over-reliance, excessive cognitive offloading, reduced independent reasoning and self-regulation development).
  • Calls for longitudinal research, common conceptual definitions, and learning environments that balance external support with independent problem solving.

Connected Concepts

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Citation

S, P., Joseph, J., Jose, M., S. M, A., N, R., & Joseph, J. (2026). Artificial intelligence as a cognitive partner: a developmental framework for human-AI co-regulation in learning. Frontiers in Developmental Psychology, 4, 1835258.