Curriculum Theory and Pedagogy for Student Mobility: Research and Practice in International Higher Education
Bibliographic record
Abstract
Curriculum Theory and Pedagogy for Student Mobility – an edited collection of international research – seeks to examine how curriculum theory within different social, political, and cultural contexts can be actuated to advance equity and diversity, plus supportive and inclusive outcomes in international student education. A comprehensive volume, it contours a holistic interdisciplinary landscape of the field. The book draws upon both a broad range of curriculum-related theoretical frameworks and multiple perspectives to offer a diverse spectrum of examples about the many challenges and complexities involved in not only theorizing about, but doing the work of, educating international students in institutions of higher education. Additionally, the book provides a strong pedagogical framework for enhanced teaching practices, as well as new avenues for research in international student education. Drawing upon the expertise of contributors from varied backgrounds, identities, fields, and positionalities, the assembled chapters elucidate contemporary curriculum theory and its foundations and uses and analyzes its potential in international education. Equally, theoreticians and practitioners, both, offer valuable insights into conceptualizing, strategizing, and applying curriculum theory-driven research and proven practices for the advancement of the field of international student education.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".