Scrutinizing Teachers’ Awareness of Global Citizenship Education (GCED) in Jordan
Bibliographic record
Abstract
This study aimed to determine the Global Citizenship Education (GCED) awareness level of teachers of different subjects in Jordan and to investigate whether their global citizenship awareness levels varied in terms of different demographic variables. The sample comprised 4305 teachers. Data were gathered using an awareness scale and an interview. Findings revealed that teachers showed an unsatisfactory level of awareness of GCED; females were more aware of GCED. Based on the results, it is recommended that teachers’ knowledge should be fostered in teaching GCED concepts, skills, and values, and to transcend the teacher-centered approach as it doesn’t promote the outcomes of creating global citizens. Keywords: Teachers’ Awareness, Global Citizenship Education, Demographic Variables, Teacher Development. Cette étude avait pour but de déterminer le niveau de sensibilisation à l'éducation à la citoyenneté mondiale des enseignants de différentes matières en Jordanie et d'examiner si leur niveau de sensibilisation à la citoyenneté mondiale variait en fonction de différentes variables démographiques. L'échantillon comprenait 4 305 enseignants. Les données ont été recueillies à l'aide d'une échelle de sensibilisation et d'un entretien. Les résultats ont révélé que les enseignants ont montré un niveau insatisfaisant de sensibilisation à la citoyenneté mondiale ; les femmes étaient plus sensibilisées à la citoyenneté mondiale. Sur la base des résultats, il est recommandé de renforcer les connaissances des enseignants dans l'enseignement des concepts, des compétences et des valeurs de la citoyenneté mondiale, et de transcender l'approche centrée sur l'enseignant car elle ne favorise pas la création de citoyens du monde. Mots clés : Sensibilisation des enseignants, éducation à la citoyenneté mondiale, variables démographiques, développement des enseignants.
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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 | 0.002 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".