An examination of parents' socioeconomic background, stress and value of homework as predictors of quality of homework involvement
Bibliographic record
Abstract
How parents help children with homework has important implications for academic outcomes.Research on the impact of parents' socioeconomic background (SEB) on quality of homework involvement (QHI) is inconclusive.The present study replicated methods used by Dumont, Trautwein, Nagy, and Nagengast (2014) to examine immigration status, occupational status, and education level as predictors of parents' QHI.Dumont et al. (2014) employed Self-Determination Theory as the theoretical framework in creating a student-report quality of parental homework involvement measure with parental control, structure, and responsiveness as the scales.In the present study, the QHI measure was further developed and adapted into a parent-report questionnaire to test Dumont et al.'s (2014) findings in a younger, elementary aged, sample of 81 students.In addition to examining SEB variables as predictors of QHI scales, parental stress and parental value of homework were also evaluated as predictors.The present study replicated Dumont et al.'s (2014) findings as multiple regression analyses revealed indices of SEB were not significant predictors of QHI scales.In support of the present studies hypotheses, linear regression analyses revealed higher levels of stress and viewing homework as valuable predicted greater levels of parental control and parental responsiveness, respectively.Hence, parental stress and value of homework play a more important role in influencing QHI than parents' education, occupation, and immigration status.Findings suggest parents provide higher quality homework support when their own psychological needs are addressed.Interventions aimed at facilitating students' homework experience should support the psychological needs of those providing the homework support.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".