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Record W2062590269 · doi:10.1080/1350462032000126096

Experimentation with a socio-constructivist process for climate change education

2003· article· en· W2062590269 on OpenAlexaffabout
Diane Pruneau, Hélène Gravel, Wendy Bourque, Joanne Langis

Bibliographic record

VenueEnvironmental Education Research · 2003
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsUniversité de Moncton
Fundersnot available
KeywordsEnvironmental educationProcess (computing)PedagogyClimate changeConstructivist teaching methodsSociologyPsychologyMathematics educationTeaching methodEnvironmental resource managementEnvironmental scienceEcologyComputer science

Abstract

fetched live from OpenAlex

A socio-constructivist and experiential process for climate change education was experimented within two coastal communities of Eastern Canada with 39 students 13 and 14 years of age. The pedagogical process, based on local observation of climate change, Duit's conceptual change theory (1999) and experiential learning, aimed for the improvement of students' conceptions of climate change: the nature of the phenomenon, its signs, causes, consequences and remedial actions as well as the possibility of mobilizing the population in reducing its impact on climate. Initial and final interviews with the young adolescents indicated an improvement in students' ideas about climate change's diverse dimensions. However, the students expressed their uncertainty regarding the adults' ability to change their behaviour. Students also identified educational activities that helped improve their conceptions.

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)0.041
metaresearch head score (Gemma)0.052
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.041
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0410.052
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0040.009
Scholarly communication0.0040.003
Open science0.0030.005
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.037
GPT teacher head0.399
Teacher spread0.362 · 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 designQualitative
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

Citations125
Published2003
Admission routes2
Has abstractyes

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