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dc.contributor.authorCao, Shi
dc.contributor.authorHo, Anson
dc.contributor.authorHe, Jibo
dc.date.accessioned2018-05-06T21:26:11Z
dc.date.available2018-05-06T21:26:11Z
dc.date.issued2018
dc.identifier.citationShi Cao, Anson Ho & Jibo He (2017) Modeling and Predicting Mobile Phone Touchscreen Transcription Typing Using an Integrated Cognitive Architecture, International Journal of Human–Computer Interaction, 34:6, 544-556en_US
dc.identifier.issn1044-7318
dc.identifier.otherWOS:000430073400006
dc.identifier.urihttp://dx.doi.org/10.1080/10447318.2017.1373463
dc.identifier.urihttp://hdl.handle.net/10057/15210
dc.descriptionClick on the DOI link to access the article (may not be free).en_US
dc.description.abstractModeling 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.en_US
dc.language.isoen_USen_US
dc.publisherTaylor & Francisen_US
dc.relation.ispartofseriesInternational Journal of Human–Computer Interaction;v.34:no.6
dc.subjectText entryen_US
dc.subjectPerformanceen_US
dc.subjectSkillen_US
dc.subjectTasksen_US
dc.subjectHanden_US
dc.titleModeling and predicting mobile phone touchscreen transcription typing using an integrated cognitive architectureen_US
dc.typeArticleen_US
dc.rights.holder© 2018 Taylor & Francisen_US


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