The Effect of School Design on Student Performance
Bibliographic record
Abstract
The present study aims at exploring the influence of school design on student performance. The participants consisted of 150 students who studied at two Iranian public school and private school in Mashhad City. School Design and Planning Laboratory (SDPL) model of Georgia University (and Tanner (2009)) was used as an appraisal indicator of school design and some of its design characteristics such as unrestricted and functional views, indoor and outdoor spaces, and natural life were explained to students. In addition, student performance, defined by the average of their final achievement scores, was compared to measures of school environmental characteristics. To this end, design characteristics of these schools and students’ performances have been studied. Quantitative data, subjected to a set of descriptive statistics, showed that school design was a strong factor for students of private school. In fact, the finding indicated that characteristics of physical learning space and deign of private school had fundamental effects on student performance. That is, learning space as a strong component can motivate students to study and progress.
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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 | 0.002 | 0.007 |
| 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 | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".