One brick at a time: Building a developmental profile of spatial abilities
Bibliographic record
Abstract
Spatial abilities are not only fundamental for activities of daily living, but they are also markers of academic and professional success. It has remained a challenge, however, to understand their development across childhood and adolescence, partly because of the lack of spatial tasks that are appropriate across age groups. For example, the well-established paper-based mental rotation test (MRT) has been shown to be too difficult for children. In the current study, we tested girls and boys in three age groups: younger children (5-8-years-old), older children (9-12), and adolescents (13-17) on a hands-on visuospatial task using toy bricks: the brick-building task (BBT). Children completed a low- and a high-mental rotation demand (LMR and HMR) version of the BBT and the paper-based MRT. Correlations were found between all tasks. Children, especially females, found the HMR more challenging than the LMR condition, but all children successfully completed the BBT. In contrast, the MRT was too difficult for the younger children to solve performing at chance. Given this result and that the BBT is a game-like, 3D, interactive task, the BBT could be used to examine the biological and/or environmental factors that affect the early development of visuospatial abilities.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".