More Errors vs. Longer Commands: The Effects of Repetition and Reduced Expressiveness on Input Interpretation Error, Learning, and User Preference


Many interactive systems are susceptible to misinterpreting the user's input actions or gestures. Interpretation errors are common when systems gather a series of signals from the user and then attempt to interpret the user's intention based on those signals -- e.g., gesture identification from a touchscreen, camera, or body-worn electrodes -- and previous work has shown that interpretation error can cause significant problems for learning new input commands. Error-reduction strategies from telecommunications, such as repeating a command or increasing the length of the input while reducing its expressiveness, could improve these input mechanisms -- but little is known about whether longer command sequences will cause problems for users (e.g., increased effort or reduced learning). We tested performance, learning, and perceived effort in a crowd-sourced study where participants learned and used input mechanisms with different error-reduction techniques. We found that error reduction techniques are feasible, can outperform error-prone ordinary input, and do not negatively affect learning or perceived effort.

Kevin C.. Lam
University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Carl Gutwin
University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Madison Klarkowski
University of Saskatchewan, Saskatoon, Saskatchewan, Canada
Andy Cockburn
University of Canterbury, Christchurch, New Zealand


会議: CHI 2022

The ACM CHI Conference on Human Factors in Computing Systems (

セッション: Sensing

5 件の発表
2022-05-05 01:15:00
2022-05-05 02:30:00