Features of selecting and structuring Foreign Language Teaching content in Terms of International Component
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
© 2015 Canadian Center of Science and Education. All rights reserved. Analysis of Russian curricula and textbooks for foreign language demonstrates that most of them don’t meet the requirements of education internationalization. So, the purpose of this paper is to reveal the features of foreign language teaching content selection and structuring based on the international component. The paper reveals the features of foreign language teaching content for students in the context of education internationalization which includes acquisition of knowledge that interprets the main humanity values, touches upon global problems of the modern multicultural world, cross-cultural and socio-cultural knowledge; shaping skills needed for cross-cultural communication, skills to carry out cross-cultural analysis of the interaction ways with the world around as well as formation of transcultural experience. The materials of this paper may be useful for faculty members of vocational training institutions when selecting and structuring the language teaching content as well as for further education courses of foreign language teachers.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.005 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 it