In the tested structural model, contextual support positively predicts trust calibration and collaborative regulation, trust calibration positively predicts collaborative regulation and perceived transfer gains, and collaborative regulation shows the strongest association with perceived transfer gains¶
Claim · All claims
Evidence · 1 study · associationalr2·q2
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.
q2 i? Contextual support positively predicted trust calibration and collaborative regulation in the structural model. → Fan Bu and Wei Li 2026
q2 i? Trust calibration positively predicted collaborative regulation and perceived transfer gains in the structural model. → Fan Bu and Wei Li 2026
q2 i? Collaborative regulation showed the strongest association with perceived transfer gains among the tested predictors. → Fan Bu and Wei Li 2026
Evidence¶
Fan Bu and Wei Li 2026¶
Fan Bu and Wei Li (2026). Trust calibration and perceived developmental gains in university students' collaboration with generative AI: an exploratory sequential mixed methods study. Front. Psychol. 17:1861072. https://doi.org/10.3389/fpsyg.2026.1861072
q2 · i? · associational · r2
Cross-sectional SEM survey of university students using a 22-item instrument developed from the qualitative phase; the reported structural model supported the hypothesized positive paths, with collaborative regulation showing "the strongestassociationwithperceivedtransfer gains". Standardized coefficients were not available in the provided text.
"The structural model showed that contextual support positivelypredictedtrustcalibrationandcollaborativeregulation;trustcalibration positively predicted collaborative regulation and perceived transfer gains"
Discussion¶
Learner Variables¶
- Collaboration — predictor: learners who differ on it differ in outcomes
Related Claims¶
- The direct path from contextual support to perceived transfer gains was not statistically significant, whereas the chained indirect pathway through trust calibration and collaborative regulation was significant — related
- Homogeneous problem perceptions predict better regulation outcomes in collaborative groups — related
- Co-regulation strategies were reported to create a safe, positive classroom climate and to help youth manage emotions — related
- Awareness of heterogeneous problem perceptions does not by itself predict successful regulation — related
- Schools where students report feeling more safe, supported, and challenged show stronger academic and social-emotional growth, and student reports predict future school improvement — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
sem-structural-paths-genai-collaboration-model |
title |
In the tested structural model, contextual support positively predicts trust calibration and collaborative regulation, trust calibration positively predicts collaborative regulation and perceived transfer gains, and collaborative regulation shows the strongest association with perceived transfer gains |
description |
In the tested structural model, contextual support positively predicts trust calibration and collaborative regulation, trust calibration positively predicts collaborative regulation and perceived transfer gains, and c... |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2026 |
generated |
by process:wiki-ingest on 2026-10-11 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — fan-bu-and-wei-li-2026 |
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