Standards of teacher competencies in Serbia: Comparative analysis with selected countries
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
Many countries have embarked on creating standards of teacher competencies with the ultimate goal of improving teaching in their schools. The aim of this paper is to compare Standards of teacher competencies in Serbia with those in countries/regions which perform well on PISA (Australia, Singapore, Ontario, Estonia, the Netherlands and Slovenia) in order to highlight important similarities and differences which potentially account for teacher quality in those countries, as well as inform policymakers in Serbia on how to reformulate standards of teacher competencies and, consequently, improve teacher quality and pupil outcomes. The criteria on which sets of standards in different countries are compared are: development of standards (who and how developed the standards), content of standards (subject knowledge, didactics, etc.), differentiation of standards (existence of separate sets of competencies for novice teachers, experienced teachers, etc.), purpose of standards (teacher certification, performance monitoring, career progression, accreditation of teacher education providers, etc.), and context in which the standards operate (whether they are a part of a larger framework of standards and educational practices or not). Several important differences exist between the Standards of teacher competencies in Serbia and selected countries, the greatest being the much higher level of utilisation of standards in various segments of teacher professional lives in those countries than in Serbia. Recommendations for the improvement of standards of teacher competencies in Serbia are drawn.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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