Modeling and Predicting Mobile Phone Touchscreen Transcription Typing Using an Integrated Cognitive Architecture

ABSTRACT

Modeling typing performance has values in both the theory and design practice of human–computer interaction. Previous models have simulated desktop keyboard transcription typing performance; however, as the increasing prevalence of smartphones, new models are needed to account for mobile phone touchscreen typing. In the current study, we built a model for mobile phone touchscreen typing in an integrated cognitive architecture and tested the model by comparing simulation results with human results. The results showed that the model could simulate and predict interkey time performance in both number typing (Experiment 1) and sentence typing (Experiment 2) tasks. The model produced results similar to the human data and captured the effects of digit/letter position and interkey distance on interkey time. The current work demonstrated the predictive power of the model without adjusting any parameters to fit human data. The results from this study provide new insights into the mechanism of mobile typing performance and support future work simulating and predicting detailed human performance in more complex mobile interaction tasks.

Additional information

Notes on contributors

Shi Cao

Shi Cao received the PhD degree in industrial and operations engineering from the University of Michigan, Ann Arbor, MI, USA, in 2013. He is an Assistant Professor with the Department of Systems Design Engineering, University of Waterloo, Waterloo, ON, Canada. His research interests include human performance and workload modeling, transportation human factors, and human–computer interaction.

Anson Ho

Anson Ho received his MASc degree in Systems Design Engineering from University of Waterloo in 2017. He is currently a Program Manager at Microsoft. His research interests include user interface design, user experience design, and web development.

Jibo He

Jibo He has a PhD degree in Engineering Psychology from University of Illinois and Bachelor degrees from Peking University. He is the director of the Human Automation Interaction Lab at Wichita State University. His research interests include human factors, driver distraction, eye movement, human–machine interaction, usability, and mobile devices.