Effects of hand drift while typing on touchscreens
Bibliographic record
Abstract
On a touchscreen keyboard, it can be difficult to continuously type without frequently looking at the keys. One factor contributing to this difficulty is called hand drift, where a user's hands gradually misalign with the touchscreen keyboard due to limited tactile feedback. Although intuitive, there remains a lack of empirical data to describe the effect of hand drift. A formal understanding of it can provide insights for improving soft keyboards. To formally quantify the degree (magnitude and direction) of hand drift, we conducted a 3-session study with 13 participants. We measured hand drift with two typing interfaces: a visible conventional keyboard and an invisible adaptive keyboard. To expose drift patterns, both keyboards used relaxed letter disambiguation to allow for unconstrained movement. Findings show that hand drift occurred in both interfaces, at an average rate of 0.25mm/min on the conventional keyboard and 1.32mm/min on the adaptive keyboard. Participants were also more likely to drift up and/or left instead of down or right.
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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 | 0.003 | 0.038 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".