Mobile Phone Text Entry
| dc.contributor.author | Butts, Lee | |
| dc.date.accessioned | 2017-10-31T00:59:51Z | |
| dc.date.available | 2017-10-31T00:59:51Z | |
| dc.date.issued | 2001 | en |
| dc.description.abstract | The rapid growth of Short Message Service (SMS) text messaging has meant that a fast and efficient text input method is a very important aspect of a mobile phone interface. The best way to test a new method is an empirical evaluation, but this is a time consuming and complex task. An alternative would be to predict the performance of a new method using a prediction model. Previous prediction models and evaluations of current text entry methods are discussed. The previous models have been shown to be highly inaccurate. A new prediction technique is presented that uses pilot study data and text analysis instead of the complex mathematical formulas of previous techniques. Predictions for the multi-press with next and T9 input methods are compared to the actual performance results of an empirical evaluation. The empirical evaluation also compares the performance of the newer T9 system to that of the more common multi-press method. T9 was significantly faster when entering sentences containing only dictionary words. However, the two methods were not significantly different when entering a mix of sentences that contained dictionary and non-dictionary words. As T9 remembers non-dictionary words that a user enters, it was concluded that T9 was the better method. Subjective data re- flected this with 60% of subjects stating that they preferred T9 over multi-press. The prediction technique was found to be too inaccurate to be useful to interface designers. The main failing of this and previous techniques appears to be the inability to accurately predict the mental preparation factor of the text entry actions. Further work to develop a method to calculate such values is needed. | en |
| dc.identifier.uri | http://hdl.handle.net/10092/14571 | |
| dc.language | English | |
| dc.language.iso | en | |
| dc.publisher | University of Canterbury | en |
| dc.rights | All Right Reserved | en |
| dc.rights.uri | https://canterbury.libguides.com/rights/theses | en |
| dc.title | Mobile Phone Text Entry | en |
| thesis.degree.grantor | University of Canterbury | en |
| uc.college | Faculty of Engineering | en |