TY - GEN
T1 - Modelling error rates in temporal pointing
AU - Lee, Byungjoo
AU - Oulasvirta, Antti
PY - 2016/5/7
Y1 - 2016/5/7
N2 - We present a novel model to predict error rates in temporal pointing. With temporal pointing, a target is about to appear within a limited time window for selection. Unlike in spatial pointing, there is no movement to control in the temporal domain; the user can only determine when to launch the response. Although this task is common in interactions requiring temporal precision, rhythm, or synchrony, no previous HCI model predicts error rates as a function of task properties. Our model assumes that users have an implicit point of aim but their ability to elicit the input event at that time is hampered by variability in three processes: 1) an internal time-keeping process, 2) a response-execution stage, and 3) input processing in the computer. We derive a mathematical model with two parameters from these assumptions. High fit is shown for user performance with two task types, including a rapidly paced game. The model can explain previous findings showing that touchscreens are much worse in temporal pointing than physical input devices. It also has novel implications for design that extend beyond the conventional wisdom of minimising latency.
AB - We present a novel model to predict error rates in temporal pointing. With temporal pointing, a target is about to appear within a limited time window for selection. Unlike in spatial pointing, there is no movement to control in the temporal domain; the user can only determine when to launch the response. Although this task is common in interactions requiring temporal precision, rhythm, or synchrony, no previous HCI model predicts error rates as a function of task properties. Our model assumes that users have an implicit point of aim but their ability to elicit the input event at that time is hampered by variability in three processes: 1) an internal time-keeping process, 2) a response-execution stage, and 3) input processing in the computer. We derive a mathematical model with two parameters from these assumptions. High fit is shown for user performance with two task types, including a rapidly paced game. The model can explain previous findings showing that touchscreens are much worse in temporal pointing than physical input devices. It also has novel implications for design that extend beyond the conventional wisdom of minimising latency.
UR - http://www.scopus.com/inward/record.url?scp=85015108118&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85015108118&partnerID=8YFLogxK
U2 - 10.1145/2858036.2858143
DO - 10.1145/2858036.2858143
M3 - Conference contribution
AN - SCOPUS:85015108118
T3 - Conference on Human Factors in Computing Systems - Proceedings
SP - 1857
EP - 1868
BT - CHI 2016 - Proceedings, 34th Annual CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
T2 - 34th Annual Conference on Human Factors in Computing Systems, CHI 2016
Y2 - 7 May 2016 through 12 May 2016
ER -