Direct and Indirect Impact of Perceived School Climate upon Student Outcomes
Bibliographic record
Abstract
This research aims at investigating and comparing the direct and indirect impact of children’s perceptions of school climate upon their academic performance and socioemotional adjustment. A model was developed in which children’s perception of school climate was considered as the independent variable and student academic performance and socioemotional adjustment as the dependent variables. Within this model, three mediating variables were selected which were children’s perceptions of parental involvement, academic motivation and student academic engagement. The mediators indicate three broad categories, i.e., school, home and student-specific variables, which facilitate comparing the significance of their role in the model. Data was collected from 324 students from Grades 7 and 9 and only the complete data from 268 cases (girls=126, boys=142) was analyzed. Two independent models were tested through path analysis. Findings revealed differential roles of the selected mediators for the student outcomes. This study presents a significantly useful model to understand the impact of school climate and provides baseline information for the implementation of the National Education Policy (2009), which focuses upon the improvement of learning environment of the schools. On the basis of findings, conclusion and recommendations have been presented.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".