The Relationship Between Dialectical Thinking and Emotion Understanding in Senior Preschool Children
Bibliographic record
Abstract
This study aims to clarify the methodological status of the category “activity Theoretical foundations of the relationship between child’s cognitive and emotional development were formulated in the works of Russian and international authors. We consider a child's dialectical thinking genesis as one of the cognitive development lines. This research aimed to study the relationship between dialectical thinking and emotion understanding in older preschool children. It was assumed that there is a significant relationship between emotion understanding and the success of children in completing three particular dialectical tasks, such as overcoming contradictions, understanding the simplest developmental processes and making a creative product. This study included 148 children, aged 5—6. We evaluated the level of non-verbal intelligence, dialectical thinking and emotion understanding using the following techniques: “Raven’s Coloured Progressive Matrices”, “Drawing an unusual tree”, “Cycles”, “What can be both at the same time?” and the Russian version of the “Test of Emotion Comprehension”. Correlational analysis of the resulting data revealed significant relationships between non-verbal intelligence, indicators of dialectical thinking and the overall level of emotion understanding. When controlling non-verbal intelligence, linear hierarchical regression analysis was used to demonstrate a significant contribution of dialectical thinking to the dispersion of values according to the general level of emotion understanding. The research results are of practical importance and make it possible to use transforming (understanding the simplest developmental processes and making a creative product) and overcoming contradictions as developmental tasks when working with children aged 5—6.
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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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".