Number and domain both affect the relation between executive function and mathematics achievement: A study of children’s executive function with and without numbers.
Bibliographic record
Abstract
Magnitude processing and executive functions (EFs) have emerged as robust predictors of mathematics achievement. However, the nature of these associations is still unclear. For example, it is uncertain if EFs applied in the context of domain-specific mathematical cognition (i.e., EFs applied while processing numbers) are more closely related to mathematics achievement than EFs applied in nonnumerical, domain-general contexts. Also, how distinct EF domains-that is, working memory, inhibitory control, and cognitive flexibility-and contents-that is, numerical versus nonnumerical-moderate the association between magnitude processing and mathematics achievement has not been fully understood. To address these issues, we investigated how magnitude processing, EFs applied to nonnumerical and numerical task stimuli, and their interactions were associated with mathematics achievement. Three hundred fifty-nine Brazilian third- to fifth-grade (8-10 years old) students completed measures of working memory, inhibitory control, and cognitive flexibility with numerical and nonnumerical task versions, nonsymbolic and symbolic magnitude comparison, and mathematics achievement. A series of regression models indicated that nonsymbolic and symbolic magnitude processing are consistently associated with mathematics achievement, even when controlling for working memory, inhibitory control, and cognitive flexibility measured with both numerical and nonnumerical contents. All EF measures were associated with mathematics achievement. However, cognitive flexibility measured with numerical content showed the strongest association. Results support the hypothesis that magnitude processing and EFs are uniquely associated with mathematics achievement. Furthermore, EFs measured with nonnumerical and numerical contents related differently to mathematics achievement, even when controlling for symbolic and nonsymbolic magnitude processing, suggesting they encompass somewhat distinct cognitive processes. (PsycInfo Database Record (c) 2024 APA, all rights reserved).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".