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Record W4378900866 · doi:10.15354/sief.23.or249

Trends and Issues in Science Education in the New Millennium: A Bibliometric Analysis of the JRST

2023· article· en· W4378900866 on OpenAlexaboutno aff
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Bibliographic record

VenueScience Insights Education Frontiers · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PublishingWeb of scienceDescriptive statisticsBibliometricsScience educationSociologySocial sciencePolitical scienceMathematics educationLibrary sciencePsychologyComputer scienceGeographyMEDLINEMathematics

Abstract

fetched live from OpenAlex

As a real time socio-scientific issue, the COVID-19 pandemic has clearly shown us the need for the public to understand science. As experts have repeatedly stressed in recent years, science education plays an important role in developing scientifically literate societies. In this context, it is critical to consider which subjects science educators frequently concentrate on and the messages they give to researchers, policymakers, and other stakeholders. Therefore, the purpose of this study was to use bibliometric data to understand the topics that the articles in the Journal of Research in Science Teaching (JRST), one of the flagship journals about science education and teaching, focused on over the last 20 years. This study employed both descriptive and bibliometric analysis. Based on data from the Web of Science (WoS), descriptive analyses are presented as frequencies and percentages and we used VOSviewer software for bibliometric analysis. Findings showed that more than 80% of the authors of the JRST are from the United States, Australia, Canada, and the United Kingdom. Moreover, results of these analyses demonstrate that the researchers publishing in the JRST focused on two main ideas over the past 20 years: “Which science teaching methods and strategies are most effective?” and “What can be done to make science teaching more inclusive?” As a result, it can be clearly seen that JRST has special attention on inclusive approach in science education which should be designed to include traditionally underrepresented groups.

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
gemmaBibliometrics
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Observationallow
gptBibliometrics
Domain: not available · Genre: Review
About the Canadian research system: no · About a Canadian topic: no
Observationalhigh
models agreeAgreement compares identical category sets and study designs across arms.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesBibliometrics
Consensus categoriesBibliometrics
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.617
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0590.420
Science and technology studies0.0010.002
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.027
GPT teacher head0.375
Teacher spread0.348 · 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.

Study designObservational
Domainnot available
GenreEmpirical · Review

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

Citations5
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueScience Insights Education FrontiersSame topicEducation and Critical Thinking DevelopmentCategoryBibliometricsFrench-language works237,207