Dynamic Testing of Children’s Series Completion Ability: Cognitive Flexibility as a Predictor of Performance
Bibliographic record
Abstract
<p>Dynamic testing aims to explore a child’s potential to learn by assessing improvement after training. In this study we investigated the relationship between performance on a dynamic test of series completion and children’s cognitive flexibility. This was done using a pre-test-trainingpost-test control-group design with 95 children, aged 6-8 years (<em>M</em> = 7;1, <em>SD</em> = 12.5 months). All children were tested with a measurement of cognitive flexibility. Half of the children were trained in series completion according to a graduated prompting model, while the other half only practiced. Based on initial ability and performance change after training, children were classified as non-learner, learner or high performer. The results showed that training improved series completion performance more than practice-only. Cognitive flexibility predicted static pre-test performance and instructional needs during training and might therefore be of importance in the assessment of learning potential.</p>
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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 teacher head, 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".