Bilingvalno obrazovanje i vaspitanje na školskom i predškolskom nivou u Srbiji i u svetu
Bibliographic record
Abstract
This paper, first of all, gives an overview of theoretical-pedagogical and other assumptions on teaching in school and preschool bilingual education. It gives an overview of some of the currently applied didactic-methodological, curricular and other solutions of this kind in countries where the practice of bilingual education has recently come to life, includ- ing Serbia, where it is practiced today in numerous state or private kindergartens and schools, especially in larger towns, i.e. in environments where it is easier to find educators who speak foreign languages. Some important requirements for educators and teachers regarding their language competencies that qualify them for educational work in one of the foreign languages are considered, such as competence in both certain subject and the foreign language in which it will be taught, the skill in terms of cooperation between the subject teacher and foreign lan- guage teacher, etc. Also, empirical indicators on the efficiency of bilingual teaching in foreign and domestic practice are discussed, such as research projects on the effectiveness of bilingual teaching in the world that have been aimed at determining how much it has contributed to the level of development of student competencies, with most of such research being conducted in Canada, Finland and Germany. Some of the benefits of bilingual education include better results of bilingual students when compared to non-bilingual peers in all language skills (speaking, lis- tening, reading and writing in English, French and German), higher motivation levels, a richer lexical fund, more skills of knowledge transfer, language spontaneity, intercultural awareness, cognitive flexibility and creativity, etc. However, it has been concluded that, given that there are not many dilemmas of a scientific-theoretical nature regarding the earlier inclusion of preschool children and students in various forms of institutional bilingual education, it is unsustainable that bilingual education is still an educational novelty in Serbia, and that, judging by the insignificant number of preschool institutions and schools in Serbia committed to bilingual education, this problem is still not given enough attention. Therefore, it would be useful, at least at the optional level, to offer university students foreign language teaching programs that would functionally train them for this type of teaching.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".