The Impact of Creativity and Intelligence on the Social Adaptation of the Students of the Faculty of Physical Education
Bibliographic record
Abstract
In periods of social change, creativity is the leading resource for human adaptation. Therefore, in the learning process, it is important to provide for the development of creativity both as a professional skill and as a general life competence. This work aims to elucidate the features of the formation of creativity and intelligence of students in connection with their position in interpersonal relationships. We measured various creative abilities of 224 students of the Faculty of Physical Education (a set of tasks from the tests of creativity by Torrance and Guilford); general intelligence (Raven’s Progressive matrices) and sociometric status (Moreno’s method, the criteria of educational achievements, informal-emotional communication and sports team leadership were used). It is shown that in the learning process, students significantly increase the level of general intelligence, verbal and practical (everyday) creativity increases. The uneven dynamics of the manifestations of different types of creativity depending on the stage of learning was revealed: during periods of intense adaptation, a redistribution of cognitive efforts to achieve more significant and relevant goals was observed. Eight different types of combinations of creative abilities and general intelligence that determine the diversity of students’ adaptation strategies have been identified. Direct correlations and nonlinear relationships between the severity of various cognitive abilities and sociometric status are described. The balance of intellectual and creative processes, their effective use in various situations of interpersonal interaction is the key to gaining social authority.
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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 | 0.000 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".