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Record W4283167250 · doi:10.5539/hes.v12n3p47

Educational Philosophy Adopted by Pre-Service Science Teachers

2022· article· en· W4283167250 on OpenAlexvenueno aff
Oktay Bektaş

Bibliographic record

VenueHigher Education Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsScience educationMathematics educationPhenomenology (philosophy)Constructivist teaching methodsPsychologyCreativityScientific misconceptionsTeaching methodPedagogyNature of ScienceSociologyEpistemology

Abstract

fetched live from OpenAlex

This study aims to examine the thoughts of fourth-year pre-service science teachers about the nature of science. For this purpose, the study preferred the qualitative research method and phenomenology design. Participants consisted of nine pre-service science teachers. Participants wrote a self-evaluation report after the nature of the science course. I collected data with this report and focus-group interview. I did the data analysis using content analysis. The current study discusses validity and reliability. As a result of the analysis, pre-service science teachers stated that they learned the nature of science by adopting the constructivist philosophy. Therefore, they described that they will use the constructivist scientific language when they become teachers in the future. They argued that students should learn how scientific knowledge changes and develops. In addition, pre-service science teachers emphasized that teachers should direct their students’ learning processes according to the constructivist philosophy considering scientists’ culture, beliefs, and prior knowledge. They stated that students should understand the socio-cultural impact on the learning process. They also mentioned that students should use their imagination and creativity so that they can learn scientific information meaningfully. Based on these results, I suggested that teaching based on positivist philosophy would not remove the obstacles to students’ learning science.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.284
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0050.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.000

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 head0.126
GPT teacher head0.463
Teacher spread0.337 · 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 designNot applicable
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

Citations1
Published2022
Admission routes1
Has abstractyes

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