Knowledge, Perceptions and Attitudes on Education for Sustainable Development of Pre-Service Early Childhood Teachers in Greece
Bibliographic record
Abstract
Education for Sustainable Development (ESD) is an important issue for the education of students worldwide becauseit offers knowledge, skills, attitudes and values necessary to ensure a sustainable future for humanity at local andglobal levels, which is nowadays becoming critical. The decade 2005-2014 called ‘Decade of ESD’ was an initiativeby the United Nations to promote ESD worldwide, followed currently by the Agenda 2030. ESD should be anongoing subject for students in formal and informal education, at all educational levels, and in life-long learningprograms, starting with early childhood education. This paper reports on the knowledge, perceptions and attitudes ofpre-service early childhood teachers of the University of Ioannina, Greece, on ESD using a quantitative approachutilizing a questionnaire. Our findings showed that most pre-service teachers had knowledge on environmentalaspects but did not consider societal and financial matters to be aspects of ESD. Furthermore, most students hadnever ESD lessons during their formal education. Our findings depict that pre-service students believe that ESD is animportant issue, that it should be included in the curricula and that lessons on EDS during their studies woulddevelop their ability to teach ESD to their 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".