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Record W2976007630 · doi:10.5539/ies.v12n10p37

Beliefs About Scientific Creativity Held by Pre-Service Science Teachers in the State of Kuwait

2019· article· en· W2976007630 on OpenAlexvenueno aff
Hamed Jassim Alsahou, Ahmad Shallal Alsammari

Bibliographic record

VenueInternational Education Studies · 2019
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityCuriosityEnthusiasmNature versus nurturePsychologyMathematics educationExploratory researchScience educationPedagogyEmpirical researchCreativity techniqueSocial psychologySociologySocial scienceEpistemology

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.364

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.058
GPT teacher head0.452
Teacher spread0.394 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations13
Published2019
Admission routes1
Has abstractyes

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