Title of article :
UseMe: Usable Predictive SMS Systems
Author/Authors :
Daniel K. S. Su، نويسنده , , Edy Chandra، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2009
Pages :
19
From page :
3
To page :
21
Abstract :
The uses of mobile phones have increased tremendously over the years. Nowadays, people use mobile phones more than just for making phone calls. Short Message Service (SMS) is one of the popular services among the mobile phone users. However, few studies have been done to create usable predictive text entry systems on SMS. Thus, we designed and proposed UseMe SMS predictive systems as to provide predictive list while users are typing. The UseMe SMS predictive systems minimise the number of key presses and time needed to enter text in more than one languages or users preferred languages. This has relatively increased better users personalisation and overall users performance. We evaluated the UseMe SMS predictive systems against usability core attributes which are effectiveness (successful prediction rate), efficiency (Word per Minute (WMP) and Keystroke per Character (KSPC)), and users satisfaction (SUS scores). The evaluation results exemplified that effectiveness was rated as 89.20%, WMP was 11.6220, KSPC was 0.8650, and the mean of System Usability Scale (SUS) scores was 71.50 respectively. In addition, we safely believe that the UseMe SMS predictive systems have created a promising way to substitute the current SMS text entry systems.
Journal title :
eMinds: International Journal on Human-Computer Interaction
Serial Year :
2009
Journal title :
eMinds: International Journal on Human-Computer Interaction
Record number :
679432
Link To Document :
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