COMPARATIVE ANALYSIS of TOP-PERFORMING COUNTRIES in PISA and TURKIYE’S TEACHER COMPETENCES
Bibliographic record
Abstract
The aim of this study is to compare the teacher competency frameworks (TCFs) of top performing countries in PISA (Singapore, Hong Kong, Estonia, Canada) and Türkiye and to reveal the similarities and differences among teacher competences of these countries. Comparative education method was used in the study. Successful countries in PISA from different regions were chosen as sample countries. Official documents on teacher education and specifically TCFs of sample countries were examined as the main data sources. Descriptive analysis was used for the analysis of data. This study revealed that “subject matter knowledge and pedagogical skills, teachers’ continuous professional development and collaboration, and supporting student development” are the in common competences in all sample high-achieving countries’ TCFs including Türkiye. However, “Techno-pedagogical skills” domain, which is quite important in today’s world, exists only in Estonia’s TCF. It was seen that publishing year of TCFs differs greatly. It was concluded that sample countries’ TCFs have similarities largely while there are also some differences among them. Finally, it was seen that Türkiye’s TCF shows similarities to sample top-performing countries’ TCFs to a great extent.
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How this classification was reachedexpand
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.003 | 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 teacher head, 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".