Co-creating environmental and sustainability education courses: the possibilities and pitfalls of collaborative course design
Bibliographic record
Abstract
Purpose Collaboration is critical for navigating environmental and sustainability issues; however, translating this competency into participatory approaches to environmental and sustainability education (ESE) remains elusive. The process of designing ESE courses represents an under-examined space for modeling this transformative practice at higher education institutions (HEIs) toward sustainability. This paper aims to examine barriers, enablers and outcomes of course co-creation, including co-teaching, co-designing and co-learning, to support transformative ESE. Design/methodology/approach Using a collaborative autoethnography-inspired approach, this paper critically re-examines the authors’ co-creation efforts across four ESE courses. It structures their analysis around the personal, political and practical “spheres of transformation for sustainability” (O’Brien and Sygna, 2013). Findings The paper presents how the authors’ values and worldviews, their collaborative and pedagogical practices and the institutional policies that framed their course design and teaching interacted to support or hinder transformative approaches to ESE. The outcomes highlight: the power of identifying and refining shared values; the transgressive potential of translating these values into codesign processes; the need for coproductive agility to navigate stuck systems; and the institutional barriers that need to be transformed. Practical implications This work offers concrete practices to transform ESE course and program design by addressing opportunities in the personal, political and practical spheres and sharing obstacles to transformation. Originality/value The paper offers insights into disrupting the ESE course design process and the systemic barriers that impede such participatory contributions at HEIs. It contributes to the literature on co-creation as an important aspect of transformative ESE that can foster sustainability transitions.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".