Twenty-first Century Education: Transformative Education for Sustainability and Responsible Citizenship
Bibliographic record
Abstract
Abstract Many ministries of education focus on twenty-first century education but unless they are looking at this topic through a sustainability lens, they will be missing some of its most important elements. The usual emphasis on developing skills for employability in the current global economy begs the question whether the global economy is itself sustainable over the course of this century. According to the World Business Council on Sustainable Development (WBCSD) whose membership comprises 29 of the largest, most important companies on the planet, it is not. Continuing on the current development path would require approximately 2.3 planets earth to support existing levels of resource and energy use, and waste production, projected out for a global population which will reach 9 billion by 2050. And yet most discussions of 21st century education are premised on servicing, rather than transforming, the current global economy. This paper explores the opportunities and benefits of connecting the discourse on twentyfirst century education with Education for Sustainable Development (ESD) which seeks to prepare learners for the varied and interrelated environmental, social, and economic challenges they will meet as they confront a changing world. ESD emphasizes futures thinking and strategic planning that will enable learners to help create and flourish in a more sustainable economy. Conventional teaching models must also shift to a “transformative” style of education for the twenty-first century in order for humankind to learn how to live more sustainably on this planet.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.020 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.004 | 0.006 |
| 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".