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Record W2983855727 · doi:10.5430/ijhe.v9n1p44

Perceptions and Attitudes towards Sustainable Development among Malaysian Undergraduates

2019· article· en· W2983855727 on OpenAlexvenueno aff
Balamuralithara Balakrishnan, Fumihiko Tochinai, Hidekazu Kanemitsu

Bibliographic record

VenueInternational Journal of Higher Education · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Education and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsCornerstonePerceptionSustainable developmentSustainabilitySocial responsibilityEducation for sustainable developmentPsychologyPublic relationsSocial sustainabilityPolitical scienceQuestionnaireFocus groupEnvironmental educationEconomic growthMedical educationSociologyBusinessPedagogyMarketingSocial scienceMedicineGeographyEconomics

Abstract

fetched live from OpenAlex

This paper reports the findings of the perceptions and attitudes towards sustainable development among Malaysian undergraduates. The study was carried out involving 154 undergraduates from five universities in Malaysia. This research was conducted based on a survey whereby the respondents were given a questionnaire to gauge their perception and attitude towards sustainable development. The output of the analyses showed that the respondents have positive perceptions and attitudes towards all sustainability dimensions—environmental, economic, and social—except for economic and social bound issues. These findings suggest that the educators who are involved in sustainable development education need to focus on economic and social bound aspects. Overall, the findings showed that the sustainable development education in higher education institutions has cultivated an appropriate sense of responsibility towards sustainability among their undergraduate students. As such, this investigation serves as a cornerstone to which the current paradigm of sustainable development education can be examined for further improvement by related stakeholders.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.993

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)0.0080.000

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 head0.006
GPT teacher head0.278
Teacher spread0.272 · 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.

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

Citations57
Published2019
Admission routes1
Has abstractyes

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