The relation of autonomous motivation to grades is curvilinear, with grades accelerating at higher autonomous motivation¶
Claim · All claims
Evidence · 1 study · associationalr2·q3
Currency · newest study 2021 · checked against its sources 2026-10-23 (automated, 1 of 1 entry) · 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.
q3 i? In the full polynomial model, both the linear and quadratic terms of autonomous motivation positively and significantly predicted grades, indicating an accelerating rate of increase. → Mouratidis 2021
Evidence¶
Mouratidis 2021¶
Mouratidis, A., Michou, A., Sayil, M., & Altan, S. (2021). It is autonomous, not controlled motivation that counts: Linear and curvilinear relations of autonomous and controlled motivation to school grades. Learning and Instruction, 73, 101433. https://doi.org/10.1016/j.learninstruc.2020.101433
q3 · i? · associational · r2
Sample 1 full polynomial regression: autonomous motivation squared was a significant positive predictor (b = 1.95, p < .01, from Table 2). In Sample 2, autonomous motivation squared also predicted grades (b = 1.94, p = .044). Both samples' surfaces were mildly convex with highest estimated grades at high autonomous and low controlled motivation. No standardized effect size is printed for the quadratic term.
"In that model both the linear and curvilinear relations of autonomous motivation to grades were positive and statistically significant. This finding suggests an accelerating rate of increase in grades"
Discussion¶
Learner Variables¶
- Motivation — predictor: learners who differ on it differ in outcomes
Related Claims¶
- Autonomous motivation positively predicts subsequent school grades in both middle and high school students — related
- Across 37 countries, polynomial models with nonlinear or interactive effects of autonomous and controlled motivation on mathematics achievement always fit better than linear additive-only models — related
- In 3 countries, a quadratic-effects-of-x-and-y polynomial explained 7.2% of achievement variance (an 11% increase over the linear model) — related
- In 8 countries, a non-parallel asymmetric congruence/incongruence polynomial explained a modest 4.1% of achievement variance yet a 41% increase over the additive model — related
- For Han students, metacognitive knowledge followed a quadratic (accelerating) growth model while vocabulary breadth followed a linear growth model, and initially high vocabulary knowledge predicted faster later vocabulary growth — related
- Quadratic latent growth fits MAP longitudinal achievement data better than linear growth across ten states — related
- In 12 countries, a level-dependent incongruence polynomial with free cubic effect of control explained 7.8% of achievement variance (a 30.9% increase over the additive model) — related
Page metadata
| Field | Value |
|---|---|
type |
claim |
id |
curvilinear-autonomous-motivation-grades |
title |
The relation of autonomous motivation to grades is curvilinear, with grades accelerating at higher autonomous motivation |
description |
The relation of autonomous motivation to grades is curvilinear, with grades accelerating at higher autonomous motivation |
status |
review |
evidence_strength |
moderate |
newest_evidence |
2021 |
source_checked |
2026-10-23 |
generated |
by process:wiki-ingest on 2026-10-23 |
trust |
unverified — no one has confirmed this page's content |
sources |
1 — mouratidis-2021 |
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