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Record W2221597136 · doi:10.5539/jel.v5n1p31

Secondary School Biology Teachers’ Perceptions of Scientific Creativity

2015· article· en· W2221597136 on OpenAlexvenueno aff
Grace C. W. Ndeke, Mark I.O. Okere, Fred N. Keraro

Bibliographic record

VenueJournal of Education and Learning · 2015
Typearticle
Languageen
FieldPsychology
TopicCreativity in Education and Neuroscience
Canadian institutionsnot available
Fundersnot available
KeywordsCreativityCurriculumMathematics educationPopulationPerceptionClass (philosophy)PsychologyPedagogyMedical educationSociologyMedicineComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

<p class="Default">The purpose of this study was to investigate secondary school biology teachers’ perceptions of scientific creativity. Cross-sectional survey research design was employed. The population of the study comprised all biology teachers in public secondary schools in Kericho and Kajiado counties in Kenya. A sample of 205 biology teachers’ was selected from a population of 347 using proportionate random sampling technique. A Biology teachers’ questionnaire was used to collect data. Data were analyzed using descriptive statistics. The findings show that a high percentage of the biology teachers have correct perceptions of general creativity but only a small percentage have the correct perceptions of scientific creativity. The findings have also yielded valuable information that informs curriculum developers, teacher trainers and policy makers that the majority of teachers have inadequate perceptions of scientific creativity and this may influence their classroom practices. It is recommended that science teacher education programmes emphasize scientific creativity in their methodology courses to empower teachers to provide learning opportunities that would enhance learners’ creativity in science lessons. Curriculum developers also need to prepare curriculum materials that include more classroom activities that enhance scientific creativity. <strong></strong></p><p class="Default"><em><br /></em></p>

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.092
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.412
Teacher spread0.354 · 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.

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

Citations14
Published2015
Admission routes1
Has abstractyes

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