Competence-Based Readiness of Future Teachers to Professional Activity in Educational Institutions
Bibliographic record
Abstract
The purpose of the scientific treatise is to investigate and intensify competence-based readiness of future teachers to professional activities in educational institutions, namely, the interrelated competencies of leaders’ communication competence (LCC) and communication components of global competence (GC). To do this, jigsaw activities & opinion sharing methods were applied to the educational environment of the students of the experimental group. In the process of achieving the goal of research the following methods were used: qualitative-quantitative and contrastive-comparative analysis of the obtained experimental data, statistical-mathematical interpretation of empirical data and their functional analysis, ascertaining experiment method and educational experiment method. The results of the educational experiment prove that on average the representatives of the experimental group managed to score 11.9 points more (9.6%) in accordance with the developed diagnostic paradigm of advanced communicative traits of modern teacher. The improvement of communicative competencies in the behaviour component was the most noticeable within the communication components of GC. The result is 10.0% higher in the experimental group, especially regarding the Skills component both within the LCC (10.3% higher in the experimental group) and within the communication components of GC (the difference here was 17.5%). The applied methods confirmed the positive effect on the development of vocationally orientated communicative competencies of student teachers.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".