University Students’ Perception toward Global Citizenship’s Knowledge, Skills and Values in the Sultanate of Oman
Bibliographic record
Abstract
Global citizenship refers to a sense of belonging to a larger culture and humanity in general. It emphasizes the people's political, economical, social, and cultural interdependence and interconnection at the local, national, and global levels. This study explores university students’ perceptions toward global citizenship knowledge, skills, and values in the Sultanate of Oman. To achieve this objective, a descriptive approach was followed by developing a questionnaire including 47 items covering three major dimensions of global citizenship education, namely cognitive, socio-emotional, and behavioral (CSeB). The questionnaire was tested to ensure its validity and reliability and applied to a study sample of 299 students (122 males and 177 females). The findings show statistically significant differences at (α=0.05) between the mean of students’ responses who studied Global Citizenship Course (GCC) and those who did not. This reflects the effectiveness of the GCC on students’ points of view. Also, the findings show a significant difference between students’ points of view regarding the accommodation variable in the cognitive domain in favor of students who live with their families compared with those who live on-campus. GCC plays a significant role in developing student skills and pro-social behavior. The effort to establish a concept of global citizenship is a small step towards a better understanding of its impact and effect.
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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 | 0.001 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".