<i>My Creative World (MCW)</i> : Improving Creative Thinking in Elementary School-Aged Children
Bibliographic record
Abstract
Many training programs have aimed to improve creative thinking abilities in various settings. The study of relevant literature revealed a relatively lower number of creativity programs for children than those developed for adults. The current work introduces a new and comprehensive nine-week long creativity intervention program implemented (out of school-setting) in 8- to 11-year-old children of socioeconomically disadvantaged families in Turkey. The intervention program was organized around four main themes (Persona, Object, Surrounding, Experience) and composed of nine activities: collection making, identity box, building a memory-device, designing an object, sensory mapping, designing a space, visual storytelling, exploring an imaginary planet, and solving a social conflict. Children (n = 159) were randomly assigned to experimental and control groups, and they took the Torrance Tests of Creative Thinking both before and after the intervention. Results showed that children in the experimental group had significantly higher verbal fluency and originality scores at the posttest compared to the control group. These results provide further evidence for the trainability of creativity and introduce a novel, affordable creativity intervention program that is feasible enough to be implemented in and out of the school setting.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".