Personally Oriented Model of the Educational Process: Subjectively Essense Focus
Bibliographic record
Abstract
The article proves that globalization, informatization, openness and standardization of the education quality have radically changed not only the scheme of knowledge transfer, teaching methods, but also have actualized the problem of understanding the deep essence of knowledge itself, its levels. The emphasis is placed on the priorities of cultural and personal knowledge, which are an integral part of the personality and provide with the expansion of his/ her social experience. It is substantiated a significance of the educational knowledge formation as a synthesized set of philosophical principles, humanitarian knowledge, pedagogical experience, which are designed to overcome the inconsistency and diversity of two types of «products»: «production of a cultural person» in education and «production of knowledge» about the structure and basic processes of education. It is stated that the positions of a synergetic approach allow to analyze the development and functioning of the educational system both in the short and long perspective, to create favorable conditions in the educational environment for choosing and giving each subject a chance to move individually, to stimulate independence of choice and making a responsible decision, to provide personal development and educational knowledge, the formation of skills of knowledge self-management of as the basis of professional competence.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.016 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".