Controlling-Supportive Homework Help Partially Explains the Relation between Parents’ Math Anxiety and Children’s Math Achievement
Bibliographic record
Abstract
Previous research has shown that math homework help of higher-math-anxious parents impedes children’s math learning and facilitates the development of math anxiety. In the present study, we explored a possible explanation for this phenomenon by examining the relations between parents’ math anxiety, their math homework-helping styles (i.e., autonomy- and controlling-supportive), and their child’s math achievement. Parents of children ages 11 to 14 completed an online survey. Using path analysis, we examined the relations among parental factors (i.e., math anxiety, math ability, and homework-helping styles) and child math achievement. Parents’ math anxiety was positively related to both autonomy-supportive and controlling-supportive math homework-helping styles. Notably, controlling-supportive style partially mediated the relation between parents’ math anxiety and their children’s math achievement. Thus, it is possible that the use of a controlling-supportive math homework-helping style may explain why the homework help offered by higher-math-anxious parents is detrimental to their children’s math learning. Identifying negative relations between parent factors and children’s math outcomes is crucial for developing evidence-based math learning interventions.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".