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| Content Provider | ACM Digital Library |
|---|---|
| Author | Tarasewich, Peter Gong, Jun |
| Abstract | The creation of text will remain a necessary part of human-computer interaction with mobile devices, even as they continue to shrink in size. On mobile phones, text is often entered using keypads and predictive text entry techniques, which attempt to minimize the effort (e.g., number of key presses) needed to enter words. This research presents results from the design and testing of alphabetically-constrained keypads, optimized on various word lists, for predictive text entry on mobile devices. Complete enumeration and Genetic Algorithm-based heuristics were used to find keypad designs based on different numbers of keys. Results show that alphabetically-constrained designs can be found that are close to unconstrained designs in terms of performance. User testing supports the hypothesis that novice ease of learning, usability, and performance is greater for constrained designs when compared to unconstrained designs. The effect of different word lists on keypad design and performance is also discussed. |
| Starting Page | 211 |
| Ending Page | 220 |
| Page Count | 10 |
| File Format | |
| ISBN | 1581139985 |
| DOI | 10.1145/1054972.1055002 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2005-04-02 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Predictive keypad text entry Mobile device user interface design Novice learning and usability |
| Content Type | Text |
| Resource Type | Article |
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