The Status of Science and Technology Relative to Other School Subjects. Results of a Study Conducted on Primary and Secondary School Students in Quebec
Bibliographic record
Abstract
Background:In recent decades, many studies have examined students’ interest in science and technology (S&T) at school. However, few investigations have studied this interest in a manner that accounts for the status that students assign to this subject relative to other subjects in the curriculum. The main objective of this article is to conduct such an examination.Material and methods:This study that used a questionnaire included 2,571 students.Results:reveals that S&T occupies an intermediate position relative to other subjects, with only slight differences between boys and girls. However, there are important differences across school years: 1) S&T is perceived to be increasingly difficult as students’ progress in their schooling; 2) relative preference for S&T decreases during the primary-secondary school transition but subsequently rises; and 3) the relative importance of S&T increases compared with all other subjects as students advance in their education. Significant correlations are observed between the latter two dimensions and students’ intentions to pursue studies or careers in S&T.Conclusions:The hierarchization of the curriculum has a significant impact on students' interest for S & T and on the intention to pursue studies in the field
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".