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Record W2964690139 · doi:10.5430/ijhe.v8n4p202

Teacher Canditates’ Environmental Awareness and Environmental Sensitivity

2019· article· en· W2964690139 on OpenAlexvenueno aff
Emine Zehra Turan

Bibliographic record

VenueInternational Journal of Higher Education · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental educationSensitivity (control systems)Scale (ratio)Dimension (graph theory)Significant differencePsychologyEnvironmental impact assessmentGeographyPedagogyEngineeringMathematicsEcologyStatisticsBiologyCartography

Abstract

fetched live from OpenAlex

Teachers have a huge effect on raising students' environmental awareness and helping them develop sensitivity to environmental issues. The aim of this study was to examine the environmental awareness and environmental sensitivity of teacher candidates. In the study, “ Environmental Awareness and Environmental Sensitivity ” scale developed by Timur and Yılmaz (2003) for teacher candidates (277) was used as data collection tool. Descriptive analysis method was used for data analysis by SPSS program. As a result of the study, it was determined that there was no significant difference between the branches and the genders of Environmental Awareness and Environmental Sensitivities of candidates teachers. A significant difference was found between the branches in the Environmental Sensitivity dimension of the scale. Teacher candidates’ Environmental Awareness and Environmental Sensitivity do not change according to their gender. It was found that Religious Culture and Ethics Teaching teacher candidates had a higher score in terms of environmental sensitivity.

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)0.001
metaresearch head score (Gemma)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.021

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.005
GPT teacher head0.262
Teacher spread0.258 · 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

Citations13
Published2019
Admission routes1
Has abstractyes

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