Οι στάσεις των μαθητών για τις φυσικές επιστήμες: τέσσερις χώρες, ένα μοντέλο
Bibliographic record
Abstract
Using a structural equation model this research study investigated the student attitudes towards science of the 8th grade students in Cyprus. This study proposes a model of the effects of educational background of the family, school climate, reinforcement and teaching on student attitudes toward science. Through the use of LISREL, a structural equation model was developed with data obtained from the TIMSS-R 1999 database, the model contains three exogenous constructs -the educational background of the family, the reinforcement and school climate- and two endogenous constructs -leaching and student attitudes. The study demonstrated that reinforcement and school climate influence teaching; the family's educational background, the environmental reinforcement: and the school climate influence student attitudes toward science, and teaching has direct effect on science attitudes, in general, the Cyprus model fits the data from Australia, Canada, and Korea, although there are some minor differences among them.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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; 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".