Partnerships Between Teacher Education Universities And Schools In Practicum To Train Pre-Service Teachers Of Vietnam
Bibliographic record
Abstract
Teacher education universities and schools have traditionally been the main sites of teacher learning in Vietnam. This relationship is the key in the process national curriculum innovation. The purpose of this research is to determine the relationship between teacher education universities and schools in Vietnam, in regard to partnering for the delivery of teacher education adapting national curriculum innovation in Vietnam. Data will be collected through questions involving 243 participants comprising student teachers, university lecturers and mentors. The result of this paper also uses semi-structured interviews to draw conclusions. The findings show that there is a model for teacher education universities - schools cooperation in teacher preparation. However, the partnership is limited by such factors such as planning, mentoring, practicum, teacher education universities visits to schools, communication and inconsistencies that seemed to characters the relationship. The findings suggest that the partnership between pedagogy universities and schools can be enhanced by recognizing the interdependent nature of the relationship, the diversification of areas of universities - schools joint activity, and increased closely conversations between the partners about problems which are suitable to the arrangement. The result of the research may provide insights into factors that focus on undermining the effectiveness of partnerships, as well as the implications of these for the professional development of prospective teachers.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".