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Record W4402821866 · doi:10.1080/13504622.2024.2403398

An exploration of parents’ engagement with learning about climate change through science education: learnings for future practice

2024· article· en· W4402821866 on OpenAlexfundno aff
Nicola Broderick, Órla Kelly, Clíona Murphy, Karen Kerr, Joan Whelan

Bibliographic record

VenueEnvironmental Education Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
FundersQueen's UniversityScience Foundation IrelandQueen's University Belfast
KeywordsEnvironmental educationClimate changePedagogyOutdoor educationScience educationSociologyPsychologyEcology

Abstract

fetched live from OpenAlex

Climate change education is crucial to addressing the climate crisis. Studies show that parents and guardians can play an important role in transmitting knowledge, competencies, and a pro-environmental orientation to their children. Whilst climate change education can span many disciplines, it has been effective within science education. In this paper we embrace evidence-based effective approaches to science education, with parents. Climate change education research literature published to date focusses on school-based interventions and there is a dearth of literature on parental involvement. This paper describes the development of, and outcomes associated with, a programme to promote engagement with climate change education for families from socioeconomically disadvantaged backgrounds. Data were gathered through post semi-structured interviews and reflections on posters and photos created and collected throughout the programme. Findings indicate that this approach engaged parents in climate change education with their children and successfully addressed various misconceptions. The programme presents a real opportunity to engage parents in their children’s formal 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 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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.694
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.006
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.069
GPT teacher head0.430
Teacher spread0.361 · 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 designOther 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
Published2024
Admission routes1
Has abstractyes

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