Predicting task execution time on handheld devices using the keystroke-level model

The Keystroke-Level Model (KLM) has been shown to predict skilled use of desktop systems, but has not been validated on a handheld device that uses a stylus instead of a keyboard. This paper investigates the accuracy of KLM predictions for user interface tasks running on a Palm OS based handheld device. The models were produced using a recently developed tool for KLM construction, CogTool, and were compared to data obtained from a user study of 10 participants. Our results have shown that the KLM can accurately predict task execution time on handheld user interfaces with less than 8% prediction error. Author Keywords Keystroke-Level Model, cognitive modeling, task execution time, handheld device. ACM Classification H5.m. Information interfaces and presentation (e.g., HCI): Miscellaneous.

• Type: Conference
• Year: 2005
• Where: CHI
• Authors: Lu Luo, Bonnie E. John
• Keywords: CHI 2005, Handheld Device, Handheld User Interfaces, Human Computer Interaction, Task Execution Time