Professional competencies in the model of forming a professional-subjective attitude of the medical university students
Bibliographic record
Abstract
The article deals with the categories of competency as the ability to apply knowledge, skills and personal qualities for successful and future professional activities and students’ professional-subjective attitude as an integrative personality trait, manifested in the willingness to master professional experience and based on the independent development of professional and personal qualities through initiative inclusion in creative professionally oriented activities. The formation of a professional-subjective attitude provides the basis for the development of professional competencies, which, in turn, are the key goal and the result of the educational process. The paper proposes a model for the formation of the professional-subjective attitude of the medical university students. The motivational, cognitive, professional-practical and professional-medical components are distinguished. The motivational component includes the motivation of a student to learn, to get a profession, to form a professional-subjective attitude and also involves self-estimation of the attitude by the student himself. The cognitive component considers the process of forming a professional-subjective attitude in the student’s educational activity (moreover, this process is conscious). The professional-practical component involves the formation of a professional-subjective attitude of students through activities in the educational environment attitude and problems solving.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".