Children’s visual attention in street-crossing tasks: insights from virtual reality and eye tracking
Bibliographic record
Abstract
This study examined visual attention in children's street-crossing behaviour using a virtual reality (VR) environment with integrated eye-tracking. We hypothesized that older children would spend more time and a higher proportion of time focusing on vehicles, that boys would spend less time looking at vehicles than girls, and that greater visual attention would be associated with fewer dangerous crossings. A total of 377 children aged 7 to 10 completed six VR street-crossing trials, during which their gaze behaviour was recorded and analysed using linear regression. Results showed that older children spent a higher proportion of time looking at vehicles, indicating developmental improvements in attention. Boys spent less total time focusing on vehicles. Greater visual attention to vehicles was associated with fewer dangerous crossings, underscoring its role in pedestrian safety. These findings highlight developmental differences in gaze and the importance of attention to traffic-relevant elements.
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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".