MétaCan
Menu
← Back to cohort
Record W7162026445 · doi:10.82308/48788

Evaluating the effectiveness of environmental education essential elements in school field trip programming

2005· dissertation· en· W7162026445 on OpenAlexaboutno aff
Mariam Futer

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental educationField tripTRIPS architectureField (mathematics)Test (biology)Primary educationEnvironmental impact assessment

Abstract

fetched live from OpenAlex

This thesis investigated the apparent effectiveness of environmental education essential elements in school field trip programming. First, the elements essential to environmental education field trips were identified from the literature. Second, these elements were incorporated into a questionnaire that was administered as a pre/post test to elementary school students visiting an extensive indoor environmental education facility located in Montreal. Finally, 24 environmental education programs at eight institutions in Montreal were observed to investigate the extent and methodology of implementation of the essential elements. With regard to the chief institution, it was concluded that (1) the educational programming appeared to significantly increase environmental knowledge, and (2) the environmental attitudes were most strongly correlated with student background. Program observation at the eight institutions demonstrated that a wide array of environmental topics was presented, but there was insufficient instruction of environmental issues and action strategies. The list of observed implementation methodologies and the study conclusions could prove useful as a research-based foundation for effective environmental education field trip program development.

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)0.006
metaresearch head score (Gemma)0.036
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.036
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.008
GPT teacher head0.340
Teacher spread0.333 · 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 designObservational
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
Published2005
Admission routes1
Has abstractyes

Explore more

Same topicEnvironmental Education and Sustainability→French-language works237,207→