Assessing Children’s Computational Skills: Validation of an Adapted Version of the Canadian Achievement Test - Second Edition for 10 year olds
Bibliographic record
Abstract
This study tested the validity of the mathematic subtest of the Canadian Achievement Test – Second Edition (CAT/2; Canadian Test Centre, 1992) for 10 year olds, adapted from the original version administered at age 8. The analyses showed satisfactory internal consistency of the adapted version at age 10, and slightly higher internal consistency than that of the original version at age 8 (.81 vs .76). The total scores distribution of the age 10 version were slightly negatively skewed, suggesting that the tool is sensitive to assess children with lower mathematic abilities. Using a correlational design, the results showed substantial cross-age convergent validity between the age 8 and age 10 versions (.49, p < .001), and cross-measure convergent and discriminant validity of this adapted version. We conclude that the adapted mathematics subtest of the Canadian Achievement Test could be used to reliably measure children’s computational skills at age 10.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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".