Forming Future Teachers’ Aesthetic Culture in Foreign Educational Practice
Bibliographic record
Abstract
Abstract The article deals with a theoretical analysis of foreign educational experience in solving scientific problems of forming future teachers’ aesthetic culture. Given the current socio-cultural situation, it has been noted that a teacher who developed his/her aesthetic culture can make a direct contribution to the social and cultural challenges of a changing world. Based on the study of scientific and pedagogical literature, normative and legal support and the content of practical courses, the author has revealed the peculiarities of forming future specialists’ aesthetic culture in foreign countries (Japan, Germany, Canada, the United States, England). Special attention has been paid to the aesthetic potential of fine arts in forming future teachers’ aesthetic culture, which ensures the harmony of intellectual and aesthetic development of personality, enriches the emotional and sensual sphere, develops cognitive and creative activities, aesthetic needs and tastes, stipulates for future teachers’ involving in the process of artistic and aesthetic culture of the nation. The performed analysis proves that the forming of future teachers’ aesthetic culture should be based on the intercultural approach; the ideas of interrelation between aesthetic and ecological in aesthetic education; integration relations between powerful potential of fine (visual) arts, environmental science and aesthetic creativity. The experience of foreign educational practice may be adopted by domestic universities to form individual aesthetic culture of future 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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.004 | 0.006 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.000 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".