What are they counting on? An investigation of the role of working memory in math difficulties in elementary school-age and university students
Bibliographic record
Abstract
Math difficulties (MD) are nearly as common as difficulties with reading. Despite this, MDs have received much less attention from researchers and we have yet to define a core cognitive process for MD. Knowledge about a core cognitive process would assist with early identification and remediation of MDs. Working memory has been identified as one cognitive process that is strongly associated with math difficulties. Most research examining the association between working memory and math calculation skills has been predicated on Baddeley and Hitch’s (1974) multicomponent model of working memory. Results of studies are inconclusive with respect to which component of Baddeley and Hitch’s model is most associated with math calculation skills. The wide variety of tasks that have been used to measure the components of Baddeley and Hitch’s model may be one reason for the lack of consistent findings. In the Introduction, common tasks used to measure the components of Baddeley and Hitch’s model are described and discussed. The Automated Working Memory Assessment Battery (AWMA) is suggested as a measure that adequately assesses all components of Baddeley and Hitch’s model. The AWMA was used in two studies examining the role of the components of working memory in math calculation skill in elementary-school (Study 1) and university (Study 2) students. Participants in Study 1were 94 (42 female) elementary-school children (M age = 9 years 1 month; Range 6 years 0 months – 11 years 8 months). Participants in Study 2 were 42 university students (M age 20 years 9 months; Range 18 years 6 months to 22 years 11 months). In both studies, the visuospatial sketchpad (short-term visuospatial memory) emerged as the component of working memory that explained the most variance in math calculation scores. In elementary-school children, phonological processing was also important. Evidence points to a developmental path emphasizing both verbal and visuospatial skills in math calculation skills of younger children and a more specific role for visuospatial memory in adults (university students). Explicit instruction using visuospatial strategies in the teaching of math calculation skills will be important at all ages.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".