Measuring the Effectiveness of Education for Sustainable Development Interventions for Effecting Change in Knowledge, Attitude and Behaviors toward Sustainable Development
Bibliographic record
Abstract
The question addressed by this study is whether an intervention involving a brief, focused seminar providing Sustainability Fundamental education can affect change in sustainability-centric behavior via measured change in attitude toward sustainability and/or change knowledge of sustainability fundamentals. This study focused on applying and extending lessons from a previous exploration of the relationships between sustainable behavior and both attitude toward sustainability and knowledge of sustainability. The test involved determining whether brief, science-based sustainability fundamentals seminars are an effective intervention for affecting the favorable sustainable behavior of practicing engineers, defined as professionals engaged in engineering post-completion of their formal studies, in comparison to non-engineers. The principle assumption of this project is that members of the engineering community at-large, have had limited or no direct experience with formal education for sustainable development, typically due to completing their education prior to the incorporation of education for sustainable development as an academic focus area. The first part of this two-part study involved completing a cross-sectional survey to establish control group data for developing a representative understanding of the general community's knowledge of sustainability concepts, attitudes toward sustainability, and sustainable behaviors. The survey method involved collecting anonymous input from self-electing participants associated with a candidate pool targeted for regional control and demographic representation. The second part of the study involved delivering Sustainability Fundamentals seminars to a representative test group who completed both pre & post-seminar surveys to measure the seminars impact on knowledge of sustainability concepts, attitudes toward sustainability, and sustainable behaviors. The principal goal of the study was to determine whether Sustainability Fundamentals seminars are an effective intervention for impacting knowledge, attitude and favorable behavior toward sustainability. A practical goal of this study was to further develop the sustainability metrics necessary to measure favorable sustainability behavior and both attitudes toward sustainability and knowledge of sustainability.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.033 | 0.101 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".