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Record W3007905591 · doi:10.5430/wje.v10n1p102

Examination of Preservice Teachers’ Perceptions about Evolution Course

2020· article· en· W3007905591 on OpenAlexvenueno aff
Zeha Yakar

Bibliographic record

VenueWorld Journal of Education · 2020
Typearticle
Languageen
FieldArts and Humanities
TopicEvolution and Science Education
Canadian institutionsnot available
Fundersnot available
KeywordsTurkishMathematics educationPsychologyCourse (navigation)PerceptionTeacher educationScience educationPedagogy

Abstract

fetched live from OpenAlex

This is a study that explored 117 Turkish preservice science teachers’ views about evolution course. The data for the study were collected through a questionnaire that has open-ended questions. The preservice science teachers answered the questions by filling out the questionnaire at the beginning and end of the evolution course. Most of the preservice science teachers stated that they had many misconceptions and prejudice about the theory of evolution before taking this course. However, after taking it, they noticed that the theory of evolution is not only about human ancestors but it is related to all living things. Another important result of this study, as they have stated many times, evolution was a very interesting theory for them, and since meeting the theory, they had been asking too many questions to themselves and wondering and doing lots of research on it. All these results of this study show that evolution course was successful in engaging the preservice science teachers in evolution and enhancing their learning.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.043
GPT teacher head0.293
Teacher spread0.250 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2020
Admission routes1
Has abstractyes

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