Integration of Contemporary Art into Educational Programmes as a Means of Forming a Creative Personality
Bibliographic record
Abstract
The integration of contemporary art into educational programmes is becoming increasingly popular, particularly in the context of creative learning. This trend is associated with changes in educational approaches. The purpose of this paper is to analyse the impact of integrating contemporary art into educational programmes on the formation of a creative personality. The paper uses experimental research with the implementation of qualitative, quantitative, and comparative approaches. For the experiment, a matrix of methods for using contemporary art in the educational process was developed. The results of the study demonstrate the significant impact of art on the educational process. Thanks to the use of modern technologies, interactive methods and the involvement of professional artists, this experimental study confirmed the positive impact on the experimental group. Compared to the control group, the participants involved in the art-integrated curriculum showed higher levels of creative activity, creative thinking and emotional engagement. Conclusions - Education, along with the integration of contemporary art, actively contributes to the formation of modern competencies. Such interdisciplinarity helps students to discover new cultural horizons and find their own artistic path. The results of the proposed work demonstrate the need for further development of interdisciplinary approaches in education. Contemporary art contributes to the formation of creative, creatively thinking citizens who are open to modern world trends.
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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 | 0.003 | 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 | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".