How do parents and school staff conceptualize parental engagement? A primary school case study
Bibliographic record
Abstract
Understanding what different stakeholders mean by “parental engagement” is vital as school leaders and policy makers increasingly turn to parental engagement to improve pupils’ outcomes. Yet, to-date, there has been little examination of whether parents’, teachers’, and school leaders’ conceptions of parental engagement match those used in research and policy. This case study used online questionnaires to explore the conceptions of parental engagement held by 103 parents and 40 members of staff at one large English primary school. The results showed that only a quarter of school staff conceptualized parental engagement in relation to learning at home and that school leaders appeared to overestimate the impact of school-based activities. This is at odds with previous research suggesting that it is parental engagement with learning in the home – rather than parents’ involvement with school - that is associated with pupil attainment. This suggests that there might be a striking mismatch in the way that parental engagement is conceptualized by researchers advocating for its efficacy, and by school staff devising and implementing parental engagement initiatives. It is vital to raise awareness of this possibility amongst practitioners, researchers, and policy makers because any such mismatch could result in the misdirection of time and resources and the undermining of parental engagement’s potential as a powerful tool for raising attainment and closing achievement gaps.
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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 | 0.020 | 0.031 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.015 | 0.008 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| 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".