Bibliographic record
Abstract
In this paper, methodological and organizational aspects of applying CLIL methodology in teaching computer science for students of universities are analyzed. It is shown that European countries, as well as the United Kingdom, the United States of America, and Canada, where part of the curriculum has been taught in a foreign language for several decades, are most actively introducing content and language integration and promoting an interdisciplinary approach to education. CLIL methodology features and benefits are identified, namely, a comprehensive focus, stimulating learning environment, authenticity, active learning, gradual learning and collaboration. The peculiarity of CLIL methodology is that its use requires a stable elementary skill in the grammar of a foreign language, as well as knowledge of subject-specific language. In accordance with various conditions, CLIL model can be presented in various forms: it can be a full course of a foreign language discipline, a module from a specific topic area, a part of any course, a project, a laboratory workshop, and a research, too. The paper presents a plan for computer science lectures and labs in a foreign language, which contains seven stages, each of which is performed in English. Integration of computer science and teaching in English at the Kremenchuk Mykhailo Ostrohradskyi National University is implemented using developed bilingual course program “Computer for beginners”. The course content includes a study of the material necessary for obtaining skills in using modern ICT and a personal computer using English glossary. Conclusions are drawn regarding conditions and principles of teaching computer science in a foreign language. The scientific novelty of the work is that for the first time a comprehensive analysis of the expediency of using CLIL methodology was carried out at the Kremenchuk Mykhailo Ostrohradskyi National University. The practical significance of the work is that its results can be used for further implementation of content and language integration in Ukraine universities. The development of new content and language integrated courses with CLIL methodology for teaching courses in a foreign language is considered promising.
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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) | 0.000 | 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".