Implementing CLIL methodology in the context of Ukraine's integration into the European educational space
Bibliographic record
Abstract
This article focuses on the practical use of CLIL methodology in the content of professional education in Ukraine, considering the country’s current integration into the European educational space and professional market. The purpose of this research is to reflect the actualization of the CLIL approach in the context of higher education (for example, the project and educational activities of the staff of Poltava V. G. Korolenko National Pedagogical University). The tasks of the actual research are: - description of the features and advantages of applying CLIL approach as an option for teaching subject-related disciplines;- outline the results of international project activities in the context of CLIL implementation in to the practice of higher professional education.The authors analyze current studies, focused on CLIL issues, define and state the difference between CLIL (Content Language Integrated Learning), the Canadian practice of learning a foreign language through immersion (Language Immersion), American foreign language learning programs based on content (Content-Based Instruction) and the English-language system of education (English Medium Education/Instruction).The authors also assume that universities in Ukraine use EMI to internationalize educational offerings and attract students from abroad, or prepare students for study and work abroad, as well as to publish research results in English, and survive in an increasingly competitive educational market. The use of EMI also enables the prospect of teaching at universities and institutions worldwide, which is especially relevant in the context of the war with Russia.This article also deals with international cooperation within the framework of large-scale projects and various educational initiatives to research the conditions and features of the practical applications of CLIL methods in higher education systems.
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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 | 0.003 | 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) | 0.000 | 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".