Meaningful engagement with AI as a co-regulatory partner is more likely from middle childhood onwards¶

Claim · All claims
Evidence · 1 study · theoretical r2 · q1
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person

Subclaims¶

Reading the evidence codes

q is the design tier, i the impact, n the sample, and the kind with its r the rigour judged within that kind: what each code means.

This claim: no standardized effect is recorded in observations/ for it yet, so no benchmark reading is possible.

q1 i? The framework applies primarily to middle childhood, adolescence, and adulthood; in early childhood, cognition remains predominantly dependent on embodied interaction and human guidance. → S P 2026

Evidence¶

S P 2026¶

S P, Joseph J, Jose M, S M A, N R and Joseph J (2026) Artificial intelligence as a cognitive partner: a developmental framework for human–AI co-regulation in learning. Front. Dev. Psychol. 4:1835258. https://doi.org/10.3389/fdpys.2026.1835258

q1 · i? · theoretical · r2

Conceptual stage-definition passage (Section 5). The authors define stages (early childhood approximately 3–6 years, middle childhood 7–11, adolescence 12–18, adulthood 18+) and state the framework focuses primarily on middle childhood, adolescence, and adulthood rather than the entire lifespan.

"meaningful engagement with AI as a co-regulatory partner is more likely to emerge from middle childhood onwards, when cognitive and metacognitive capacities are suﬃciently developed"

Discussion¶

Learner Variables¶

Age and Developmental Stage — predictor: learners who differ on it differ in outcomes

Cognitive offloading to AI during early learning can stifle development of stable knowledge and skills — related
AI scaffolding differs from human scaffolding in availability, feedback timing, and dynamic adjustment, making its developmental impact conditional — related
Dialogic competence is a prerequisite for meaningful engagement with LLM-based chatbots — related
Hippocampal engagement during problem solving rises in middle childhood and then decreases to adult-like levels by adolescence — a narrower finding that bears on this claim
Memory-based strategy use continues to increase from childhood through adolescence into adulthood — a narrower finding that bears on this claim
Inter-problem multivoxel pattern stability in the hippocampus increases from childhood through adolescence into adulthood, reaching adult-like levels by adolescence — a narrower finding that bears on this claim

Page metadata

Field	Value
`type`	`claim`
`id`	`ai-co-regulation-middle-childhood-onwards`
`title`	`Meaningful engagement with AI as a co-regulatory partner is more likely from middle childhood onwards`
`description`	`Meaningful engagement with AI as a co-regulatory partner is more likely from middle childhood onwards`
`status`	`review`
`evidence_strength`	`weak`
`newest_evidence`	`2026`
`generated`	by `process:wiki-ingest` on `2026-10-10`
`trust`	unverified — no one has confirmed this page's content
`sources`	1 — `s-p-2026`

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