A Study on the Relationship between Six-Year-Old Children’s Creativity and Mathematical Ability
Bibliographic record
Abstract
Creativity is defined as a totality of processes and a way of attitude and behavior which exists in every child to a different extent. Every child is creative owing to their nature and their perspective on life. Offering children creative environments, especially during early childhood education, affects their mathematical abilities and supports their creative thinking. The aim of this study is to investigate whether children’s creativity and mathematical abilities vary with respect to their gender and whether there is a relationship between creativity and mathematical ability. The study population includes six-year-old children attending independent kindergartens affiliated with the Ministry of Education in Ankara city center. The sampling consists of 80 six-year-old children in total, attending Sevgi Kindergarten, which was chosen randomly from among the kindergartens in the population. Data were gathered by using several instruments. These included a “General Information Form” prepared by the researchers to gather information about the children, “Torrance Test of Creative Thinking – Figural Form A” to assess children’s creativity, and the “Test of Early Mathematics Ability- 3 (TEMA-3)” to assess children’s mathematical ability. While t-test was used to determine whether children’s creativity and mathematics scores differed with respect to gender, Pearson Product-Moment Correlation Coefficient was used to analyze whether there was a relationship between creativity and mathematical ability. The results showed that children’s creativity scores differed significantly with respect to gender, but not their mathematics scores. Also, it has been found that there is no relationship between the creativity and mathematical ability of children.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".