Cognitive development and performance of 11‐, 13‐ and 15‐year olds on a soccer‐specific test of decision making
Bibliographic record
Abstract
Abstract The primary purpose of this study was to examine the effect of cognitive development, as measured by age and cognitive style combined, of 11‐, 13‐ and 15‐year‐old children on the performance of a soccer‐specific test of decision making. The children (N = 284) undertook the Group Embedded Figures Test (Witkin et al., 1971b) to determine their cognitive style: Field Dependent (FD), Field Mobile (FM), or Field Independent (FI). They were then divided into nine groups, FD, FM, and FI at each age. Analyses revealed that all of the 15‐year‐old groups were significantly better in decision‐making aptitude than the other groups, except for the FI 13‐year‐olds.The FI 13‐year‐olds performed significantly better than the FD and FM 11‐year‐olds, and FD 13‐year‐olds. It was concluded that cognitive development affects decision‐making performance. A hierarchical multiple regression analysis showed that experience and cognitive development were moderate predictors of decision‐making performance (R 2 = .25). The study also examined the claim of Pascual‐Leone (2000) that FI, FD, and FM children use different processes to solve problems. There was no evidence to support this claim. It was concluded that the better performance of the FI participants was due to better decision‐making ability rather than differences in the types of processes used for problem solving
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".