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Record W4400370112 · doi:10.31216/bdl.20240010

Korean Students’ Environmental Perceptions: Focusing on comparative analysis with Canada and Singapore

2024· article· en· W4400370112 on OpenAlexaboutno aff
Hyunjung Kim, Shinyoung Lee

Bibliographic record

VenueInstitute of Brain-based Education Korea National University of Education · 2024
Typearticle
Languageen
FieldComputer Science
TopicEducational Systems and Policies
Canadian institutionsnot available
Fundersnot available
KeywordsPerceptionPsychologyGeography

Abstract

fetched live from OpenAlex

The purpose of this study is to investigate Korean students’ perception of sustainable development. Using raw data on students’ responses to the PISA 2018, this study analyzed Korean students’ responses to items related to sustainable development and compared these results with those from Canada and Singapore. PISA 2018 student questionnaire's items related to sustainable development were reclassified into environmental awareness, self-efficacy, sense of purpose, and action. Results revealed that students’ awareness of ‘climate change and global warming’ from all three countries was higher than that of ‘global health’, and their scores for environmental awareness were higher than their environmental self-efficacy. Regarding environmental self-efficacy and sense of purpose, Korea and Singapore showed a higher response than Canada. Among the three countries, Korea showed the highest participation rate in environmental actions due to Korea’s sociocultural and institutional characteristics. Students’ perception of sustainable development showed a mostly positive correlation with science achievement, and economic, social, and cultural status (ESCS), and the correlation with science achievement was higher. These results highlight that it is possible to identify Korean students’ perception of sustainable development and suggest implications for education in sustainable 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 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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.721
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.261
Teacher spread0.247 · 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.

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
Published2024
Admission routes1
Has abstractyes

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