Examining the relation between PASS cognitive processes and superior reading and mathematics performance
Bibliographic record
Abstract
Abstract Although several studies have shown that planning, attention, simultaneous, and successive (PASS) cognitive processes—operationalized with the cognitive assessment system (CAS; Naglieri & Das, 1997)—are significant predictors of academic performance in the general population, little is known about their role among children with superior academic skills. Thus, the purpose of this study was to examine whether PASS processes can predict superior performance in reading and mathematics. We used the standardization sample of CAS ( n = 1210) and further identified children with superior reading ( n = 62) and mathematics ( n = 73) performance on Woodcock–Johnson Tests of Achievement–Revised (Woodcock & Johnson, 1989). Results of the initial regression analyses showed that the PASS processes were significant predictors of superior reading and mathematics performance. Next, a classification and regression tree approach showed that the PASS scores could classify superior or not‐superior readers and mathematicians with 89% and 82% accuracy, respectively. Theoretical and practical implications of our results are discussed.
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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 | 0.001 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".