Beliefs About Scientific Creativity Held by Pre-Service Science Teachers in the State of Kuwait
Bibliographic record
Abstract
Understanding teachers’ sentiments and views is a central goal of the educational research community; especially, understanding teachers’ beliefs which could be transferred to classroom practices. Teachers’ beliefs about creativity and how they can nurture it has been investigated in several studies, but there is a lack of studies exploring teachers’ beliefs about creativity in the science classroom. The current study aims to understand the beliefs of pre-service science teachers about scientific creativity, fostering creativity in the science classroom, the characteristics of creative students in science, and the encouraging and challenging factors. The research design has an exploratory nature based on a questionnaire consisting of 18 closed-ended questions and eight open-ended questions. 152 questionnaires were quantitatively and qualitatively analyzed. The results indicated that science is seen as a creative school subject. Participants view scientific creativity as original, useful, imaginative, and having empirical actions. Commitment, curiosity, enthusiasm, questioning, and experimenting are the characteristics of creative students in the science classroom. Other factors that encourage or hinder the process of nurturing scientific creativity were also identified. Implementations and suggestions for future study are also discussed.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".