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Text input for mobile devices: comparing model prediction to actual performance
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Source Conference on Human Factors in Computing Systems archive
Proceedings of the SIGCHI conference on Human factors in computing systems table of contents
Seattle, Washington, United States
Pages: 365 - 371  
Year of Publication: 2001
ISBN:1-58113-327-8
Authors
Christina L. James  User Interface & Usability Group, Tegic Communications, AOL Wireless, 1000 Dexter Avenue N., Suite 300, Seattle, WA
Kelly M. Reischel  User Interface & Usability Group, Tegic Communications, AOL Wireless, 1000 Dexter Avenue N., Suite 300, Seattle, WA
Sponsor
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
Publisher
ACM  New York, NY, USA
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Downloads (6 Weeks): 48,   Downloads (12 Months): 281,   Citation Count: 37
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ABSTRACT

A study was conducted to obtain performance data for entering text on a mobile phone in order to compare it to performance predictions based on two different mathematical models. Speed data was obtained for two text input methods, T9 Text Input and Multi-tap. While the direction of the results was the same for both the performance data and both model predicitons (with predictive text entry being faster than Multi-tap text entry), the results for all three differed in magnitude. Suggestions for this discrepancy are provided. In addition, in order to help shape future models, additional results are presented for both input methods to show how both accuracy and speed performance varies based on user experience and text subject matter.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Buckingham, S. An introduction to the short message service, Mobile Lifestreams Limited, www.gsmworld.com/technology/sms_success.html (2000).
 
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3
Dunlop, M. D., and Crossan, A. Dictionary based text entry method for mobile phones, in Second Workshop on Human-Computer Interaction with Mobile Devices(Edinburgh, Scotland August 1999), 5-7.
 
4
Dunlop, M. D., and Crossan, A. Predictive text entry methods for mobile phones. Personal Technologies, (2000), 134-143.
 
5
GSM Association Press Release. G-Mail growth: Global surge continues. GSM Association, Avoca Court, Temple Road, Blackrock, Co. Dublin, Ireland. www.gsmworld.com. (2000)
 
6
Grover, D.L., King, M.T., and Kushler, C. A. Patent No. US5818437, Reduced keyboard disambiguating computer. Tegic Communications, Inc., Seattle (1998).
7

CITED BY  37

Collaborative Colleagues:
Christina L. James: colleagues
Kelly M. Reischel: colleagues