The Cost of Location Switching during Visual Alerting: Effects of Experience and Age
Bibliographic record
Abstract
A study was conducted to investigate the switching cost of changing the location of a visual alert while participants performed a high intensity, multi-display task. Based on the proposition that the spatial window of attention can be extended to include relevant, though non-task-related information, it was hypothesized that response times to the alert would increase immediately following a change in location and then recover. Generally, results showed that this was not the case, but instead response time increased several minutes after the change in location and then recovered. Further investigation revealed that age and expertise (defined as experience with tasks involving multiple displays or video gaming), were strong moderators of the effect of slowed response after switching. Less experienced adults showed an immediate and significant cost that was not shown at all, or was shown later, by more experienced adults. Older adults showed a switching cost that was absent in younger adults. The results suggest that experience with a specific task, or more general video game experience, can guard against the cost associated with moving an alert to a new, relatively untrained location.
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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 | 0.008 |
| 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) | 0.001 | 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".