The cognitive effects of playing video games with a navigational component
Bibliographic record
Abstract
Sex differences in human navigation and orientation skills are among the most recognized and studied in human cognition. Numerous findings have shown sex biases on various spatial tasks, with males typically outperforming females on popular tasks such as those measuring mental rotation. Other robust sex differences can be found in video game experience and genre preference, where males tend to play more games and prefer to play games with a stronger navigational component compared to females. To date, little is known about how experience playing video games with a specific navigation component affects spatial ability. In this study we explored how sex effects are impacted when controlling for navigation-style video game experience. In a group of 1305 participants, we first analyzed sex effects on a variety of spatial tasks without controlling for video game experience. Following this, we used case-control matching to create groups for each task that did not differ significantly in their age or video game experience. We then used these matched groups to analyze the sex effects for each task while controlling for video game experience. We found that before controlling for video game experience, males significantly outperformed females on our measure of mental rotation ability. However, after accounting for video game experience, there was no significant difference in mental rotation accuracy between females and males. We also found that before controlling for video game experience, there was no significant difference between males and female accuracy on a measure of spatial perspective taking. After controlling for video game experience, we found that females significantly outperformed males in perspective taking accuracy. Our findings suggest that video game experience does change how sex effects in spatial skills are interpreted and should be considered as a relevant confounding variable.
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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 | 0.000 | 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".