Self-Development of Pedagogical Competence of Future Teacher
Bibliographic record
Abstract
Relevance of a considered problem is caused by that situation, in which appeared pedagogical education of Russia at present. Absence of clear understanding of prospect of school, of requirements to the modern teacher, of the purposes of students training in the conditions of continuous reformed education brought in pedagogical universities to loss of vision of prospect. Nowadays problems of the teacher’s training are very actual for new school. The info field changes very quickly. Taking into account these factors, it is important to organize process of training of future teachers so that it was enough received tools: methods, receptions, and ways of receiving, processing and transfer of information–in order that adequate to requirements of time to carry out the professional pedagogical activity with the greatest effect. It is possible only at combination of educational training of the student with self-development of pedagogical competence. In article the conditions necessary for formation of motivation to self-development of pedagogical competence of students are considered. And also the main conditions of process of formation of pedagogical competence of future teachers are considered.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".