Affect, Motivation, and Engagement in the Context of Mathematics Education: Testing a Dynamic Model of Their Interactive Relationships
Bibliographic record
Abstract
The present analysis aimed to test the dynamic (interactive) model of affect, motivation, and engagement (Linnenbrink, 2007) in mathematics education with a nationally representative sample. Self-efficacy, self-concept, and mathematics anxiety were indicators of pleasant and unpleasant affect. Intrinsic and extrinsic motivation were indicators of mastery and performance approach. Educational persistence and cognitive activation were indicators of behavioral and cognitive engagement. The 2012 Programme for International Student Assessment (PISA) supplied a sample of 4,978 students from the United States for structural equation modeling. The results indicated that the PISA data overall supported the dynamic model. Specifically, the PISA data completely supported the specification of the relationship between motivation and affect, largely supported the specification of the relationship between affect and engagement, but failed to support the specification of the relationship between motivation and engagement. The PISA data largely supported the specification of the mediation effects of affect on the relationship between motivation and engagement. Keywords: affect; motivation; engagement; mathematics; structural equation modeling La présente analyse visait à tester le modèle dynamique (interactif) de l'affect, de la motivation et de l'engagement (Linnenbrink, 2007) dans l'enseignement des mathématiques avec un échantillon représentatif au niveau national. L'auto-efficacité, le concept de soi et l'anxiété liée aux mathématiques étaient des indicateurs de l'affect agréable et désagréable. La motivation intrinsèque et extrinsèque était des indicateurs de l'approche de la maîtrise et de la performance. La persistance éducative et l'activation cognitive étaient des indicateurs de l'engagement comportemental et cognitif. Le Programme international pour le suivi des acquis des élèves (PISA) de 2012 a fourni un échantillon de 4 978 élèves des États-Unis pour la modélisation des équations structurelles. Les résultats indiquent que les données PISA soutiennent globalement le modèle dynamique. Plus précisément, les données PISA ont complètement soutenu la spécification de la relation entre la motivation et l'affect, ont largement soutenu la spécification de la relation entre l'affect et l'engagement, mais n'ont pas soutenu la spécification de la relation entre la motivation et l'engagement. Les données PISA ont largement soutenu la spécification des effets de médiation de l'affect sur la relation entre la motivation et l'engagement. Mots clés : affect ; motivation ; engagement ; mathématiques ; modélisation par équations structurelles.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".