A Systematic Examination of the Linguistic Demand of Cognitive Test Directions Administered to School-Age Populations
Bibliographic record
Abstract
The selection and interpretation of individually administered norm-referenced cognitive tests that are administered to culturally and linguistically diverse (CLD) students continue to be an important consideration within the psychoeducational assessment process. Understanding test directions during the assessment of cognitive abilities is important, considering the high-stakes nature of these assessments. Therefore, the linguistic demand of spoken test directions from the following commonly used cognitive test batteries was examined and compared: Wechsler Intelligence Scale for Children, Fifth Edition (WISC-V), Woodcock–Johnson IV Tests of Cognitive Abilities (WJ IV COG), Cognitive Assessment System, Second Edition (CAS2), and Kaufman Assessment Battery for Children, Second Edition (KABC-II). On average, the linguistic demand of the standard test directions was greater than the linguistic demand of the supplementary test directions. When examining individual test characteristics, very few individual tests were identified as outliers with respect to the linguistic demand of their test directions. This finding differs from previous research and suggests that the linguistic demand of the required directions for most tests included in commonly used cognitive batteries is similar. Implications for future research and test development are discussed.
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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 | 0.022 | 0.122 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".