Students’ awareness of science teachers’ leadership, attitudes toward science, and positive thinking
Bibliographic record
Abstract
There appears to be a complex network of cognitive and affective factors that influence students’ decisions to study science and motivate their choices to engage in science-oriented careers. This study explored 330 Taiwanese senior high school students’ awareness of their science teacher’s learning leadership and how it relates to the students’ attitudes toward science and positive thinking. Initial results revealed that the optimism of positive thinking is highly and positively correlated with the future participation in science and learning science in school attitudes toward science and self-concept in science. Moreover, structural equation modelling (SEM) results indicated that the subscale of teachers’ leadership with idealised influence was the most predictive of students’ attitudes toward science (β = .37), and the leadership with laissez-faire was predictive of students’ positive thinking (β = .21). In addition, the interview results were consistent with the quantitative findings. The correlation and SEM results indicate some of the associations and potential relationships amongst the motivational and affective factors studied and students’ attitudes toward and intentions to study science, which will increase their likelihood of future involvement in science careers.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".