Modeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architecture

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Date

2017-09-07

Authors

Cao, Shi
Ho, Anson
He, Jibo

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Publisher

Taylor & Francis

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.

Description

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Human–Computer Interaction on 2017-09-07, available online: http://dx.doi.org/10.1080/10447318.2017.1373463

Keywords

Transcription typing, mobile typing, interkey time, human performance modeling, QN-ACTR

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