Gender, videogames and navigation in virtual space
Bibliographic record
Abstract
Spatial abilities associated with success in educational and occupational fields of Science, Technology, Engineering, and Mathematics (STEM) have been repeatedly shown to be gendered, with males demonstrating measurably better spatial abilities than females. Less is known about why this is, or about how experience with spatial systems (videogames, for example) affects these abilities. We conducted two experiments with 82 participants with varying degrees of videogame experience on measures of mental rotation, spatial learning, and spatial memory. Spatial learning and memory were tested in a Virtual Morris Water Maze. In the first experiment, the maze lacked proximal landmarks. Males proved faster and more accurate than females in learning the location of the hidden platform. As predicted males also outperformed females in mental rotation abilities. Mental rotation correlated with performance in the virtual maze, indicating that in the absence of proximal landmarks, participants relied on strategies requiring mental rotation. Experienced 3D videogame players did not demonstrate superior spatial learning and memory, but performed better than novices in mental rotation. In the second experiment, the maze had proximal cues, in the form of landmarks on the circumference of the virtual pool, and gender-based differences in navigational performance significantly diminished. Under these changed environmental conditions, mental rotation ability did not correlate with performance in the VMWM, suggesting that given proximal cues, the need for mental rotation diminishes. Differences between videogame novices and experts also decreased when proximal cues were provided. Females in particular obtained more discernible benefits from videogame experience. Together, these experiments reveal how the spatial abilities and strategies used to solve the Morris maze task vary with environmental design. Given the structural similarities between the virtual maze and videogame environments, these results offer insight into how spatial experience gained through videogame playing can affect aspects of spatial cognition, and can help identify design elements that contribute to their improvement.
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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 | 0.000 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".