Sustainability consciousness of pre-service teachers in Pakistan
Bibliographic record
Abstract
Purpose The purpose of this paper is to draw attention towards sustainability consciousness (SC) of pre-service teachers (student teachers) as their role is central in teaching for sustainable development. This paper investigated SC of the pre-service teachers in Pakistan and compared it with other undergraduate students in the country and with that of Swedish upper secondary students. Design/methodology/approach The paper used survey method using a tool developed by a group of Canadian researchers to measure knowledge, attitudes and behaviours towards sustainable development. The instrument was later adapted by a group of Swedish researchers to measure SC. Study data came from 207 pre-service teachers and 154 undergraduate students studying humanities. Findings The paper reports that SC of the pre-service teachers in Pakistan is much lower than that of Swedish upper secondary students. Moreover, the paper indicates that the SC of pre-service teachers is not different from other undergraduate students in the country. Practical implications This paper establishes a baseline of SC of the final-year pre-service teachers enrolled in BEd (Honours) programme in Pakistan. Such a study is critical in the context when ESD is a missing element in teacher education in Pakistan. In the presence of such a baseline study, teacher education institutes and departments might review their curricula in terms of their focus on ESD and plan for initiatives to educate pre-service teachers for sustainability. Originality/value The paper contributes to a broader debate on measuring SC of university students.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".