Student's Interest in Science and Technology and its Relationships with Teaching Methods, Family Context and Self-Efficacy
Bibliographic record
Abstract
In order to explore students’ interest towards ST however, few of them perceive the utility of school-ST b) in terms of school subjects, perceived importance and preference order, ST the preference order is not, however, similar to the perceived importance order. The latter, and therefore the role of ST c) the analysis based on correlations and regressions propose some important predictors of general interest towards S&T. The results highlight, among other things, the importance for school to intervene on certain factors that promote the development of students’ interest in S&T. For instance, 1) to affirm the importance of S&T right from the beginning of elementary school, 2) to use teaching methods that allow students to establish links between what they learn in school and their lives, as well as methods centered on students’ development of inquiry processes, 3) to promote cultural activities related to S&T, and 4) to promote a positive development of self-concept through quality schooling.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".