Parents' implicit intelligence beliefs about children's intelligence: Implications for children's academic self-concept and achievement in Maths, English, and French
Bibliographic record
Abstract
In this study, we hypothesized that a higher parents' fixed mindset will lead to lower achievement in math, French and English (MEF) school subjects, but also that lower achievement in MEF will lead to a higher parents' fixed mindset. We have also tested the mediational role of academic self-concept (ASC) in the parents' fixed mindset-children's achievement relation. Participants ( n = 1046 students and their parents) have filled twice a questionnaire. Results indicate that parents' fixed mindset significantly and negatively predicted subsequent achievement in French and English, but the magnitude of these coefficients was quite low (β < | 0.07|). Moreover, most relations connecting prior ASC to subsequent achievement in MEF were not supported thereby discarding the possibility that ASC mediates the parents' fixed mindset-children's achievement relation. Overall, these results cast some doubts about the importance of parental fixed mindset for children's academic achievement and ASC. The present study tests if the effect of parental fixed mindset on achievement in Math, English, and French school subjects is explained by students' academic self-concept in these school subjects. The results showed that parental fixed mindset weakly predicts subsequent achievement in French and English and that academic self-concept does not mediate this small association. Thus, the safest conclusion is that parents' mindsets are related to their children's achievement, but so weakly that it is difficult to recommend any intervention based on parental mindsets with this research. • We test if parental fixed mindset predicts academic achievement and academic self-concept. • Parental fixed mindset predicts significantly and negatively achievement, but weakly. • These weak relations are not mediated by academic self-concept.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 source (direct Gemma or distilled Codex), 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".