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Record W1761629023 · doi:10.18497/iejee-green.01212

Cultivating Artistic Approaches to Environmental Learning: Exploring Eco-art Education in Elementary Classrooms

2013· article· en· W1761629023 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDergiPark (Istanbul University) · 2013
Typearticle
Languageen
FieldArts and Humanities
TopicArt Education and Development
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsEnvironmental educationCurriculumVisual arts educationPedagogyPlan (archaeology)The artsMathematics educationAction researchSociologyPsychologyGeographyVisual artsArt

Abstract

fetched live from OpenAlex

This article explores curriculum development in eco-art education, an integration of art education and environmental education, as a means of increasing awareness of and engagement with the environment.  It reports on a qualitative research study that tracked teachers’ experiments with the design and implementation of eco-art education in elementary classrooms.  Guided by the framework of collaborative action research, a team of educators generated practical and theoretical knowledge to plan, implement, observe and reflect on eco-art curricula and pedagogy.  As the first inquiry to examine eco-art education in a sustained way across multiple school sites, it makes a significant contribution to the emerging knowledge and growing discourse of eco-art education by demonstrating how arts-based learning at the elementary level can align with and support environmental education concepts and pedagogy. 

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.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.690
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.001

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 head0.074
GPT teacher head0.192
Teacher spread0.118 · 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