Students showed increasing metacognitive regulation across the semester, moving from copying GPT suggestions to predicting and challenging its responses¶
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Evidence · 1 study · designr2·q2
Currency · newest study 2026 · not yet checked against its sources · not reviewed by a person
Subclaims¶
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q2 i? Four metacognitive subthemes emerged: planning, monitoring, regulation, and evaluation. → Jason Zagami 2026
Evidence¶
Jason Zagami 2026¶
Jason Zagami. (2026). Generative AI as a cognitive partner: personalised GPTs and differentiated learning in undergraduate teacher education. Education Tech Research Dev. https://doi.org/10.1007/s11423-026-10746-4
q2 · i? · design · r2
Analysis of weekly reflective journals (300–400 words) across the semester; Student 8 described shifting from copying suggestions to predicting and challenging the GPT, and the article aligns the progression with Zimmerman's self-regulated learning cycle.
"Students demonstrated increasing sophistication in metacognitive behaviours across the semester. Early reflections were descriptive (“I used the GPT to explain…”). In contrast, later entries displayed strategic awareness (“I realised that adjusting the temperature setting gave me more creative responses when brainstorming assessments.”)."
Discussion¶
Learner Variables¶
- Metacognition — outcome: instruction changes it
Related Claims¶
- Within this LMS-integrated design, personalised GPT use fell into four recurring cognitive partnership roles: conceptual tutor, co-designer, reflective mirror, and cognitive challenger — related
- Within a single LLM session, students' help-seeking shifts toward answer- and verification-seeking while explicit self-regulation modestly increases — related
- Grade-9 students' LLM-supported mathematical interactions are strongly request-dominated, with little explicit planning, monitoring, or evaluation — reports the opposite
- During AI-tutor interactions, students' turns were dominated by help requests with near-absent monitoring and evaluation — reports the opposite
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
gpt-metacognitive-regulation-growth |
title |
Students showed increasing metacognitive regulation across the semester, moving from copying GPT suggestions to predicting and challenging its responses |
description |
Students showed increasing metacognitive regulation across the semester, moving from copying GPT suggestions to predicting and challenging its responses |
status |
review |
evidence_strength |
weak |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-29 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — jason-zagami-2026 |
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