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Record W4405475707 · doi:10.1515/cti-2024-0099

Reasoning in chemistry teacher education

2024· article· en· W4405475707 on OpenAlexaff
Samia Khan

Bibliographic record

VenueChemistry Teacher International · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMathematics educationChemistry educationScientific reasoningTeacher educationChemistryFacet (psychology)Science educationEmpirical researchPsychologyPedagogyEpistemology

Abstract

fetched live from OpenAlex

Abstract Research on preservice science teacher’s reasoning is comparatively new in a larger field of research on reasoning. This study examines model-based reasoning among preservice science teachers to make recommendations on how reasoning can be fostered within chemistry teacher education. It coalesces over 20 years of a program of research in this area. Firstly, several empirical studies on undergraduate students and their reasoning are examined. Future chemistry teachers are drawn from this pool of undergraduate students. Secondly, empirical studies in preservice teacher education are examined to highlight reasoning among preservice chemistry teachers. Thirdly, recommendations are put forward for future research on the development of scientific reasoning among chemistry teachers as an important facet of chemistry teacher education.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.025

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.005
Scholarly communication0.0050.002
Open science0.0010.002
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.401
Teacher spread0.370 · 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 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

Citations2
Published2024
Admission routes1
Has abstractyes

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