Perceived GenAI role is systematically associated with metacognitive dimensions activated: replacement-tool users show no evaluation or elaboration, collaborator users show predominantly higher-order activity¶

Claim · All claims
Evidence · 1 study · qualitative r3 · q2
Currency · newest study 2026 · checked against its sources 2026-10-20 (automated, 1 of 1 entry) · not reviewed by a person

Subclaims¶

q2 i? Chi-square tests showed significant between-group differences in all six metacognitive categories across the four GenAI role groups, with evaluation showing the largest effect (χ2 = 56.18, p < 0.001). → Cui 2026

Evidence¶

Cui 2026¶

Cui, Y., Yan, W., Chiu, T. K. F., & Nakajima, T. (2026). How motivation and roles influence metacognitive engagement in student-GenAI interaction. International Journal of Educational Technology in Higher Education, 23(34). https://doi.org/10.1186/s41239-026-00610-z

q2 · i? · qualitative · r3

Chi-square tests across four role groups (127 replacement-tool, 59 enhancement-tool, 74 instructor, 84 collaborator messages). The Collaborator group's M4 (35.3%), M5 (30.6%), and M6 (16.5%) together accounted for 82.4% of coded messages; the article reports M5 showing "the largest between-group effect (χ 2= 56.18, p < 0.001)". No standardized effect size is printed.

"The Replacement Tool group was almost entirely confined to M1 (31.2%) and M2 (46.9%), with M5 and M6 entirely absent."

Discussion¶

Learner Variables¶

• Self-Regulation — outcome: instruction changes it

Related Claims¶

• Intrinsically motivated students show significantly higher proportions of evaluation and elaboration messages, while extrinsically motivated students concentrate in planning and orientation — related
• Only the Collaborator group shows a complete significant sequential metacognitive chain from orientation through elaboration; the Replacement Tool group shows only self-loops — related
• Motivational orientation is strongly associated with the role students assign to GenAI: intrinsically motivated students most often position it as an instructor, extrinsically motivated students as a replacement tool — related
• Practitioners near-universally reject AI as a replacement for instructor expertise while affirming its supportive, collaborative role — related
• Role metaphors positioned GenAI as helper, learning partner, and friend/foe, with a high proportion combining friend and foe — related
• Post-training GenAI use patterns were unevenly distributed: efficient collaborators were the largest profile (47.5%), followed by over-revisers (26.2%) and mixed users (21.2%) — related
• Students predominantly conceptualize the LLM as an Assistant rather than Peer or Expert, and role distributions differ significantly across assignments — related
• Process mining shows the ChatGPT group's revision loop centred on consulting ChatGPT, while the human-expert group strengthened connections between revising and reading, orientation and evaluation — related
• Human–GenAI collaborative interactions show promise for supporting metacognition and sociometacognition, based on an exploratory expert case study — related
• Learners supported by ChatGPT, a human expert, checklist tools, or no support show no significant difference in post-task intrinsic motivation — related
• Checklist tool use significantly increases Evaluation processes, an effect not observed in the ChatGPT and human-expert groups — related