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New Data on Text Entry with Multitap and T9 Sajida Sajida

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New Data on Text Entry with Multitap and T9 Sajida Sajida New Data on Text Entry with Multitap and T9 Sajida Sajida University of Tampere School of Information Sciences Interactive Technology M.Sc. thesis Supervisor: Poika Isokoski June 2012 University of Tampere School of Information Sciences Interactive Technology Sajida Sajida: New Data on Text Entry with Multitap and T9 M.Sc. thesis, 64 pages, 6 index + appendix pages June 2012 Abstract Mobile phone technology is advancing rapidly. Text entry on mobile devices is essential as more and more people are using mobile phones for the purpose of writing text messages. The need to make mobile devices as easy to use and as efficient as possible is more acute than ever. New methods of interaction are proposed but the old ones still stay as long as they provide users with some comfort and benefit which others lack. I conducted an experiment to compare the two well-known, and till recently, most widely used text entry methods for mobile phones, the multitap and T9. Sixteen participants in two groups, experienced and novice, transcribed phrases, and the speed and error rate were measured. Statistically significant effects of text entry method, experience, and their interaction were found for text entry rate. T9 users were faster than multitap users and experienced users faster than novice. No statistically significant effects were found for error rate. In comparison to earlier data on the performance of the multitap and T9, novice and experienced users of multitap and T9 performed better with overall 10.67 wpm vs 7.95 wpm for multitap group and 18.39 wpm vs 14.72 wpm for T9 group. Table of Contents 1 Introduction.....................................................................1 2 Background......................................................................4 2.1 Mobile phone keypad layouts...................................................................................4 2.1.1 The 12-key keypad..............................................................................................5 2.1.2 Variants of the 12-key keypad.............................................................................6 2.1.3 Mobile Keypads/Keyboards With Different Layouts........................................11 2.2 Mobile Text Entry Methods .................................................................................15 2.2.1 Key-based Text Entry Methods ........................................................................16 2.2.1.1 Mobile Phone Keypad...............................................................................16 2.2.1.2 QWERTY and Other Small Keyboards.....................................................23 2.2.2 Stylus-based Text entry methods.......................................................................30 2.2.2.1 Soft keyboards ..........................................................................................30 2.2.2.2 Gesture Recognition..................................................................................33 2.2.2.3 Handwriting Recognition..........................................................................35 2.3 Summary..................................................................................................................38 3 Multitap vs T9................................................................40 3.1 Method.....................................................................................................................40 3.1.1 Participants........................................................................................................40 3.1.2 Apparatus ..........................................................................................................44 3.1.3 Procedure...........................................................................................................45 3.1.4 Dependent Measures..........................................................................................47 3.1.5 Design................................................................................................................48 3.2 Results......................................................................................................................48 3.2.1 Speed.................................................................................................................48 3.2.2 Accuracy............................................................................................................50 4 Discussion.......................................................................53 5 Conclusions....................................................................57 References...............................................................................58 Appendix..............................................................................65 Acknowledgments First of all, I thank my thesis supervisor, Prof. Poika Isokoski, whose guidance and support was always available. Among other things, not only did he offer me a topic, but also the software to run the experiment. He also helped in recruiting the participants for my experiment. I also thank all the participants who volunteered for the experiment and helped me towards the completion of my thesis. Another thanks goes to my family, especially my parents, for making me what I am. Their support and constant guidance are what I needed most and I got most. I would not have been able to do anything without their tireless effort for everything they have done for me. Last, but not least, I thank my partner for his love, help in working with software, and patience which made my work as easy as it could get. 1 Introduction Mobile phones have gone through enormous changes during the last two decades, not only in shape, size and other aspects of their physical appearance but also in their function. They are no longer used only for making and receiving calls but also for sharing pictures and videos using MMS (Multimedia Messaging Service), playing games, browsing websites, taking pictures or making videos through the built-in digital camera, playing music, GPS navigation and most of all, for textual communication using SMS (Short Message Service). Text entry on mobile phones started in the 1990’s, and in 1995 on average only 0.4 messages per GSM customer per month were sent. The situation changed, however, with the average number of messages reaching 35 per user per month by the end of 2000, [Wikipedia, 2012], and in 2010, 6.1 trillion text messages were sent around the world [Itu.int, 2010], which makes almost 96 messages per user per month. The enormous increase in the amount of text messaging on mobile phones opened a new area of research and focused the attention of researchers on developing better text entry methods for mobile phones. However, it was not easy to devise new methods of text entry on keypads small enough for mobile phones. This also gave rise to the need for inventing new and different types of keypads and key arrangements for mobile phones for the purpose of improved text entry, along with using speech and gestures for the same purpose. Despite advances in these new methods of text entry on mobile phones, physical touch-based, manual text entry techniques still dominate and are used on almost all mobile phones. 1 When developing new text entry methods, there is a need to identify which methods are better than others, hence requiring a comparison between the existing and newly developed methods. Without any data available about the efficiency of a particular method, it is hard to know if it is better, or good at all, to be adopted by users, as only experimental work can reveal many of the problems in user interfaces. The most common and adopted keypad used for mobile phones is the 12-key keypad, and the most widely used methods of text entry are multitap and T9 (the dictionary-based disambiguation method from Tegic Communications, Inc). Although there have been several other methods in use, or at least developed, such as LetterWise, TiltText and Twiddler Typing, which have been compared and evaluated empirically with either or both of these methods, to our surprise, there has not been much of a comparison between the two dominant, well known, and widely used text entry methods themselves. The only study evaluating the two methods against each other was conducted by James et al. [2001]. It obtained the performance data for text entry on mobile phones using the two methods, and compared it with the performance predictions based on two different mathematical models namely “keystroke level model” and “movement and linguistic model”. The result of the study concerning the performance data, however, showed some unexpected results. Two user groups were involved in the study, a group of novice and a group of experienced users. The mean overall text entry speed with the multitap method was unexpectedly lower for the expert group (7.93) than for the novice group (7.98). Moreover, the total number of errors committed by expert users using the multitap method was higher than that of the novice users, 116 and 65 respectively. These observations raise some doubts about the validity of the results which poses a need for further evaluation of the two methods between the two groups. Another motivation for the work in this thesis was the fact that old multitap and T9 data may not represent modern use cases. Users have gained experience in the course of 11 2 years, and any comparison based on these old data can be misleading. In order to have a better benchmark data to compare to, conducting a new experiment was essential.
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