Validation of the Student-Rated Parental School Involvement Questionnaire: Factorial Validity and Invariance Across Time and Sociodemographic Characteristics
Bibliographic record
Abstract
Studies highlighting the importance of parental involvement in schooling have multiplied over the past years. However, well-validated tools assessing the different dimensions of parental involvement are lacking, especially when addressing young students’ perception of their parents’ involvement. This study offers a preliminary validation of the Student-Rated Parental School Involvement Questionnaire (SR-PSIQ); factor structure, measurement invariance, and predictive validity were assessed. Data collected on four measurement occasions from 923 French-Canadian primary school students was used. Results favored a four-factor model (parental expectations, parent–child communication, homework supervision, and school-based involvement). The SR-PSIQ was invariant across time, student gender, parental immigration status, and socioeconomic status. Regarding predictive validity, all dimensions of parental involvement were associated with later student engagement. Overall, the SR-PSIQ is a brief, valid, and reliable instrument that can easily be used by researchers or partitioners who want to understand how parents are involved in their child’s schooling.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 | 0.012 |
| 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 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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 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".