Designing for Response Tasks: An Empirical Evaluation of Response Tasks in a Video Game Context
Bibliographic record
Abstract
Numerous studies have examined reaction time differences due to stimulus or response methods but few have examined the relationship between these factors, and even fewer in a video game context. We present a formal experiment comparing the impact of four display types across four input methods, and three indicator speeds across three target area sizes on accuracy and response time in game-like displays. Our main findings indicate a number of significant main effects across different display types, indicator speeds, and target area sizes, and many interaction effects between pairs of speeds and sizes. The vertical meter and horizontal meter were found to have a significantly faster response time than the circular meter and pulsating ring. The vertical meter, horizontal meter, and circular meter were all found to have higher average accuracy than the pulsating ring, but participants generally reported finding the circular meter the easiest to successfully respond to due to its cyclical nature. Overall, larger target sizes and faster speeds led to lower response times, and larger target sizes and slower speeds led to higher accuracy.
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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 | 0.012 | 0.151 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".