Predictive human performance modeling made easy
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Predicting task execution time on handheld devices using the keystroke-level model
CHI '05 Extended Abstracts on Human Factors in Computing Systems
Comparisons of keystroke-level model predictions to observed data
CHI '06 Extended Abstracts on Human Factors in Computing Systems
RIM: risk interaction model for vehicle navigation
Proceedings of the 10th asia pacific conference on Computer human interaction
Target orientation effects on movement time in rapid aiming tasks
HCI'13 Proceedings of the 15th international conference on Human-Computer Interaction: interaction modalities and techniques - Volume Part IV
Design and evaluation of a predictive model for smartphone selection
DUXU'13 Proceedings of the Second international conference on Design, User Experience, and Usability: web, mobile, and product design - Volume Part IV
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The Keystroke-Level Model was developed to predict accurately task execution time for mouse-and-keyboard systems. Middle-sized touch screens are becoming much more popular so it is important to determine whether KLM can provide useful predictions for these interfaces as well. The KLMs were created using special software CogTool for three touch screen interfaces for integrated control systems and were compared to experimental data. The results showed that the KLM prediction error for middle-sized touch screens reached less than 5%. This conclusion is that KLM has acceptable accuracy level in this environment for making predictions for the task execution times.