Young adolescent psychological need profiles: Associations with classroom achievement and well‐being
Bibliographic record
Abstract
Abstract Drawing on self‐determination theory, a person‐centered methodology was adopted to identify distinct pupil profiles based on their psychological need satisfaction. A sample of 586 pupils (387 male, 199 female; mean age = 12.6, range 11–15 years old) from three secondary schools reported their psychological need satisfaction, and well‐ and ill‐being, with teachers rating pupil achievement. Hierarchical cluster analysis revealed five distinct profiles. Four profiles indicated synergy existed between the three needs, showing similar in‐group levels of satisfaction across the needs but in varying amounts. Univariate and multivariate analyses, controlling for school and taught subject, revealed the satisfied group displayed the highest classroom performance ( F 4,540 = 7.03; p < 0.001; η p 2 = 0.05), well‐being ( F 8,1,136 = 45.63; p < 0.001; Wilk's Λ = 0.57; η p 2 = 0.24) and lowest ill‐being ( F 8,1,134 = 23.39; p < 0.001; Wilk's Λ = 0.74, η p 2 = 0.14), whereas the dissatisfied group displayed the most adverse outcomes. The findings illustrate that the three psychological needs may operate interdependently and should be considered in combination rather than in isolation. The research offers practical insights into why pupils may function differently in classrooms and could inform targeted initiatives towards pupils with psychological need satisfaction deficits.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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; both teacher heads agree on what is shown here.
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".