Individual and Contextual Factors Determining School Belonging of Adolescents in the UK: Evidence from PISA
Bibliographic record
Abstract
There has been long discussion in educational psychology about the individual factors that promote pupils’ sense of school belonging during secondary education. However, the literature on the school factors associated with these outcomes seems to be less informed. By utilising an ecological-systemic approach, the present study aimed to consider the predictive role of a range of individual and school factors including academic achievement, motivation, gender, class size, extracurricular resources, and type of school attended. To do this, UK data of a large, current and representative sample of 14,157 15-year-old pupils in 550 schools from the Programme for the International Student Assessment (PISA) study were analysed. Using a multi-level structural equation modelling framework, results indicated that the individual-level factors statistically significant associated with pupils’ sense of belonging were academic motivation, gender, and socio-economic status, explaining 6% of the student-level variance. School factors that predicted sense of school belonging included availability of extracurricular activities, and class size, explaining 39% of the school-level variance. Our results provide strong evidence concerning the importance of school factors that may be more malleable to change, when compared to individual factors, in determining pupils’ sense of belonging. We propose a theoretical framework that integrates the role of individual and school factors to advance knowledge concerning pathways for the development of evidence-based intervention targeting the improvement of school belonging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".