Pedagogical Support of Socio-Professional Self-Determination of Students
Bibliographic record
Abstract
Recently, the prevailing trend is that graduates do not work in their profession; the purpose of the article is to study ways to improve the effectiveness of social and professional self-determination of students. The authors conducted an empirical study of the causes of this phenomenon and identified the main ones (the choice was made for the student by his parents; in the process of studying, the student became disillusioned with the chosen profession; the chosen profession does not bring the necessary earnings; did not find a job in the speciality). The article noted that the percentage of work in the profession depends on how long ago the specialist graduated from the university. The authors identified what causes could be eliminated in the process of teaching students. Having analyzed the existing pedagogical methods for students' more confident social and professional self-determination, the authors proposed the conceptual foundations of pedagogical support for students' social and professional self-determination. These recommendations will make it possible to correct students' social and professional self-determination in their speciality. The authors proposed an algorithm that allows to visually and transparently determine the student's attitude to the chosen speciality and ways to persuade the student to look for a job and work in the profession and the necessary tools for this. The proposed dual approach to adjusting the socio-professional self-determination of students will allow them to identify the problem at an early stage, track it and fix it with adjustment. Research has shown that there are several main reasons why a student does not work in a profession. All these reasons, in our opinion, are subject to correction in the learning process. The main feature of success is the desire of the university to identify such students at an early stage, a developed adjustment mechanism and constant control and monitoring. A further promising direction of research is the development of questionnaires that can identify this problem and a mechanism for attracting artificial intelligence that can guide each student individually and signal when the university's intervention is necessary.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".