Teacher Perceptions of Education for Sustainable Development Teaching: Before and During the COVID-19 Pandemic
Bibliographic record
Abstract
This paper examines teachers' perceptions of Education for Sustainable Development regarding their practice before and during the COVID-19 pandemic. The study analyzes approaches to teaching Education for Sustainable Development and barriers faced. While teachers reported shifts in what was taught and how it was taught during the pandemic, most respondents remained committed to the core values of teaching Education for Sustainable Development. Barriers described by teachers before the pandemic included a lack of resources, time, and support, and barriers during the pandemic included a shifting and uncertain teaching environment burdened by video calls during lockdown periods and efforts to keep students safe during in-person teaching. Teacher insights included: spending regular time outdoors and framing the community as a classroom is a benefit for the health of students and their education; learning is inherently more powerful and productive when done socially; and teaching with technology has benefits but should not be the sole medium in which learning occurs. The aspects of school that were taken for granted and that were greatly diminished during the pandemic, social learning, guest speakers, field trips, and a predictable learning environment, were also those elements that were reported as being at the forefront of teachers’ plans for their students when the pandemic ended. This research may benefit teachers, school leaders, policymakers interested in Education for Sustainable Development, and scholars planning future research. Keywords: teacher perceptions, Education for Sustainable Development, COVID-19
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 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 | 0.005 | 0.014 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".