The Relation between Computerized and Paper-and-Pencil Mental Rotation Tasks: A Validation Study
Bibliographic record
Abstract
The present study aimed at validating a computerized mental rotation task developed for use in functional Magnetic Resonance Imaging (fMRI) studies. Eighty-three females and 74 males completed the computerized task, two pencil-and-paper tests of mental rotation, and reported their high school grades in mathematics, English, and history. The computerized task involved the presentation of pairs of three-dimensional stimuli that differed in orientation by 0, 40, 80, 120, or 160 degrees. Results showed significant gender differences in favor of males in the three main tasks, although gender interacted with angle of rotation in the computerized task. Evidence for concurrent validity was obtained in the form of significant correlations between performance on tasks relevant to mental rotation (paper and pencil tests and mathematics grades), whereas discriminant validity was demonstrated by a lack of correlation with tasks deemed irrelevant to mental rotation (English and history grades). These findings support the use of our computerized mental rotation task as a valid measure of mental rotation abilities in fMRI studies. This study was funded by a National Institute of Health grant (J. Imperato-McGinley, Principal Investigator). The authors are thankful to Mariana Soraggi for her assistance with data collection and scoring. We are also indebted to Michael Peters for providing the three-dimensional drawing used in the computerized task.
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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 | 0.004 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".