Communicative Competence Formation of Future Officers in the Process of Foreign Language Training
Bibliographic record
Abstract
Modernization of the military system and its content has enhanced the value of the foreign language as a subject aimed at the formation of communicative competence of future officers. It mainly concerns a professional language, which is an obligatory part of the cadets' professional training. One of the main tasks of foreign language training of future officers is to form the communicative competency in the spheres of professional and situational communication as well as to learn new professional information from foreign sources. Based on the stated above, the author developed the methodology of forming communicative competence of future officers in the process of foreign language training with the active implementation of informational communicative technologies and computer means of teaching: the virtual reality, military-professional games, role play stimulators, and other software, within which a dialogue appeared. The last is regarded as an active message exchange between participants of the educational process or a user and the information system in real-time. The use of informational communicative technologies has enabled instant access to remoted module informational resources, synchronous (asynchronous) communication between subjects of the educational process. It has also provided new opportunities for testing, administration, and cooperation. The experimental usage of the author's methodology was implemented into the teaching process of the subject “Foreign language” based on the intercultural educational environment as a set of immersion, virtual, interactive, and discourse educational environments. The analysis of the obtained results and objective consideration of the dynamics of the changes in the formation of communicative competence of future officers have been done through the integrated test (targeted monitoring, a set of adapted tests application, an online survey, a questionnaire, case study, situational modelling, individual and group interviews) and methods of mathematical statistics. The conducted study has proved the efficiency of the author’s methodology implementation based on the intercultural educational environment of higher military education establishments. The proposed methodology can be successfully used in the process of foreign language training of various specialists because its main strategic orientation is to form communicative competence and abilities for intercultural communication among students (cadets).
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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 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".