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Record W3146051553 · doi:10.5539/ies.v14n4p72

The Views of Pre-Service Science Teachers on the History of Science After Taking the Course of the Course of Nature and History of Science: A Profile from Turkey

2021· article· en· W3146051553 on OpenAlexvenueno aff
İbrahim Yüksel, Merve Eker

Bibliographic record

VenueInternational Education Studies · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMeaning (existential)Science educationQualitative researchNature of ScienceMathematics educationSociologyPsychologySocial science educationHigher educationSocial sciencePolitical science

Abstract

fetched live from OpenAlex

This study aims to determine the knowledge levels in the Nature and History of Science course of the prospective teachers studying in the science education program and their views following the course. Six interview questions were asked to the pre-service teachers in the science education program about the Nature and History of Science course. Seventy-nine pre-service teachers studying at a state university’s Faculty of Education Department of Science Education who took the Nature and History of Science course in the 2018-2019 academic year participated in this study voluntarily. Case study, one of the qualitative research designs, was used in this study. Case study is a research method that identifies an event or phenomenon within the framework of natural real life, and examines situations in a multifaceted, systematic and detailed manner (Yildirim & Simsek, 2013). The characteristics of qualitative research are based on the main emphasis, process, understanding and meaning. The researcher is the main determinant in data collection and analysis, the process is inductive, and the product should be detailed and extensive (Merriam, 2013). Data were collected through interview questions developed by the researchers on the Nature and History of Science course. According to data analysis and the views of the prospective teachers, the highest 3 frequencies for the first question are as follows: ‘Scientific information does not change. Hypotheses are developed into theories and theories are developed into laws. There is only one scientific method that is universally accepted in science.’ In the second question, the pre-service teachers named the first 5 scientists with whom they were most impressed were as Aziz Sancar, Albert Einstein, Tesla, Avicenna and Newton. As for the third question, the view mostly emphasized by the pre-service teachers on the inclusion of the Nature and History of Science course among the secondary school courses was that scientific information is not easy to reach and how to reach it should be taught. Another view was that the importance of science should be taught at an early age. The fourth question was asked to the participants to reveal the techniques/methods they will use to teach the nature of science when they actively start to work as teachers. The responses were inquiry-based teaching and constructivist learning approach along with teaching through demonstration and brainstorming. In the fifth question, while explaining the relationship between the history of science and nature of nature for science-literate individuals, pre-service teachers expressed an opinion that it is easier to understand the nature of science if it is based on the history of science, that the nature of science contains the history of science, and that the history of science and the nature of science nurture and support each other. The sixth question aimed to reveal additional views of the teacher candidates on the nature and history of science course. The responses were as follows: ‘I consider it adequate’, ‘It may be more intriguing and interesting’, and ‘The importance of science should be taught at an early age.’

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Other designlow
models splitAgreement compares identical category sets and study designs across arms.

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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.094
GPT teacher head0.447
Teacher spread0.353 · 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

Labeled directly by 2 models reading the full record.

The models applied no category: nothing in the taxonomy fit this work.

The models disagree on parts of this classification; every voice is preserved in the section at the end of the page.

Study designObservational · Other design
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
Published2021
Admission routes1
Has abstractyes

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