Children's mathematics achievement: The role of parents' perceptions and their involvement in homework.
Bibliographic record
Abstract
Two studies examined the accuracy of parents’ assessment of their children’s mathematics performance and how this relates to the time parents spend on children’s homework. Fourth, 5th, and 6th graders completed a mathematics test. Their parents then predicted their child’s test performance. Parents overestimated their children’s mathematics scores (Study 1: 17.13%; Study 2: 14.40%). The time parents spent helping their children with mathematics homework was unrelated to children’s mathematics performance, parents’ predictions of their children’s mathematics performance, and the accuracy of parents’ predictions of their children’s mathematics performance. Although increasing parents’ knowledge of their children’s mathematics competency should remediate poor mathematics performance of U.S. children, neither homework nor traditional report cards effectively inform parents regarding their children’s mathematics performance. How do parental perceptions of their children’s mathematics performance and parents’ involvement in children’s homework affect children’s mathematics performance? The interaction of these three variables has not been examined in the research on mathematics performance. The focus here specifically on mathematics ability is important given the relatively poor math ability of U.S. children in the face of the relatively high level of parental satisfaction with children’s mathematics achievement in America. The poor mathematics performance of U.S. children relative to children of other nations is well documented. In a study assessing the mathematical achievement of 13-year-olds in Korea, Spain, the United Kingdom, Canada, Ireland, and the United States, U.S. students had the lowest mean scores of any country in the study (LaPointe, Mead, & Phillips, 1989). Several studies comparing U.S., Japanese, and Chinese students have also reported the rela
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".