Preschool Children's Performance in Task Switching on the Dimensional Change Card Sort Task: Separating the Dimensions Aids the Ability to Switch
Bibliographic record
Abstract
Fifty-seven children (53% female) at 3 ages (2 1/2, 3, and 3 1/2 years) were tested on the standard Dimensional Change Card Sort (DCCS) task with integrated stimuli (e.g., a red truck) and on a separated-dimensions version where colorless shapes were presented on a colored background (e.g., a black truck on a red background). Roughly twice as many children successfully switched sorting dimensions when color was a property of the background than when color was a property of the shape itself. Children succeeded 6 months earlier in switching sorting criteria when the dimensions were separated. When evidence of both indecision and accuracy was taken into account, a clear and rich developmental progression emerged. These results support an inhibitory control interpretation of preschoolers' problems on the DCCS task. Diamond theorized that young children can have difficulty integrating features not part of a single object and separating features of a single object so that the object can be categorized first by one attribute and then by another. Preschoolers remain stuck in thinking about objects according to the objects' initially relevant attribute (attentional inertia; Kirkham, Cruess, & Diamond, 2003). To switch perspectives, the old way of thinking about the objects must be inhibited. Separating color and shape reduced the need for such inhibition; a truck was always a truck, and the background was always red.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".