Preparing Teachers to Educate for 21st Century Global Citizenship: Envisioning and Enacting
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The changing educational landscape in global context and the increasing interconnectedness and interdependence of the world place unprecedented demands on teacher education programs to prepare teachers to educate for 21st century global citizenship in K-12 schools. To chart the course of preparing global educators for an interconnected world, the Faculty of Education at University of Prince Edward Island (UPEI) Canada and UNICEF Canada have collaboratively developed an undergraduate course entitled Educating for Global Citizenship, which focuses on preparing teachers to teach for 21st century global citizenship and has been integrated as a compulsory course to UPEI's teacher preparation program. This paper is based on a three-year study examining teacher candidates' experiences in learning to educate for global citizenship, the changes of their perceptions on global citizenship education, and the challenges and achievements they experienced in educational practices. Findings from this study indicate the unique opportunities and challenges teachers face in learning to educate for global citizenship and suggest the necessity of integrating global citizenship education in teacher education program through a holistic approach. Normal 0 false false false EN-CA ZH-CN X-NONE /* Style Definitions */ table.MsoNormalTable {mso-style-name:Table Normal; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin-top:0cm; mso-para-margin-right:0cm; mso-para-margin-bottom:10.0pt; mso-para-margin-left:0cm; line-height:115%; mso-pagination:widow-orphan; font-size:11.0pt; font-family:Calibri,sans-serif; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:SimSun; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Times New Roman; mso-bidi-theme-font:minor-bidi;}
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it