When SRL is measured at a fine grain size (specific strategies), self-reports show low calibration with behavioral measures¶
Claim · All claims
Evidence · 1 study · reviewr3·q2
Currency · newest study 2019 · not yet checked against its sources · not reviewed by a person · overdue for a recheck since 2022: tool and model accuracy changes quickly
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? Studies comparing self-reports with online measures of specific SRL strategies generally indicate low calibration between the two forms of measurement. → Rovers 2019
Evidence¶
Rovers 2019¶
Rovers, S. F. E., Clarebout, G., Savelberg, H. H. C. M., de Bruin, A. B. H., & van Merriënboer, J. J. G. (2019). Granularity matters: comparing different ways of measuring self-regulated learning. Metacognition and Learning. https://doi.org/10.1007/s11409-019-09188-6
q2 · i? · review · r3
Narrative review synthesis of ten included higher-education studies comparing self-report questionnaires with online measures of specific strategies (trace data, think-alouds, eye-tracking, micro-analytic questions), concluding there is "low calibration between the two forms of measurement".
"Overall, studies that focus on the use of specific strategies when comparing self-report questionnaires with behavioral measures indicate low calibration between the two forms of measurement"
Discussion¶
Related Claims¶
- AI tools collected and organized a previously unavailable granularity of data, including individual student exchanges and classroom discussion data, to generate actionable recommendations — related
- When SRL is measured at a coarse grain size (global self-regulation), students are relatively well able to report on their strategy use — related
- Low questionnaire–think-aloud correlations may have two alternative explanations besides poor self-report ability: the methods may measure different strategies or be aimed at different tasks — related
- A task-specific questionnaire built item-by-item from a think-aloud coding taxonomy correlated r=.51 with think-aloud protocols, higher than the -.07 to .42 regularly reported — related
- The SKT-SRL shows low, mostly non-significant correlations with SRL microanalysis (online measure) — a narrower finding that bears on this claim
- Trace data tend to predict achievement better than self-reports, but self-reports of global SRL intensity can outperform traces — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
fine-grained-srl-self-reports-low-calibration |
title |
When SRL is measured at a fine grain size (specific strategies), self-reports show low calibration with behavioral measures |
description |
When SRL is measured at a fine grain size (specific strategies), self-reports show low calibration with behavioral measures |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2019 |
recheck_by |
2022 |
generated |
by process:wiki-ingest on 2026-10-19 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — rovers-2019 |
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