Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model
The Keystroke Level Model (KLM) has been utilized to predict the user behaviors and activities with desktop system. Recently, the mobile device application designers could use updated KLM model to predict the consumed time while users use mobile devices, but when designers use this method to evalua...
Saved in:
主要作者: | |
---|---|
格式: | Thesis |
语言: | English English |
出版: |
2008
|
主题: | |
在线阅读: | http://etd.uum.edu.my/765/1/Ayman_I._H._Srour.pdf http://etd.uum.edu.my/765/2/Ayman_I._H._Srour.pdf http://etd.uum.edu.my/765/ |
标签: |
添加标签
没有标签, 成为第一个标记此记录!
|
id |
my.uum.etd.765 |
---|---|
record_format |
eprints |
spelling |
my.uum.etd.7652013-07-24T12:08:55Z http://etd.uum.edu.my/765/ Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model Srour, Ayman I. H. QA76 Computer software The Keystroke Level Model (KLM) has been utilized to predict the user behaviors and activities with desktop system. Recently, the mobile device application designers could use updated KLM model to predict the consumed time while users use mobile devices, but when designers use this method to evaluate the text entry they still face some difficulties with the calculation of long equations, due to multi-tap technology. This study proposes new KLM operators to facilitate the time calculation process for text entry using traditional mobile keypad. Updated KLM operators are used to predict the user behavior in interacting with mobile devices in general and text entry in specific. The expected results contribute in estimating the consumed time accurately. 2008-11-19 Thesis NonPeerReviewed application/pdf en http://etd.uum.edu.my/765/1/Ayman_I._H._Srour.pdf application/pdf en http://etd.uum.edu.my/765/2/Ayman_I._H._Srour.pdf Srour, Ayman I. H. (2008) Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model. Masters thesis, Universiti Utara Malaysia. |
institution |
Universiti Utara Malaysia |
building |
UUM Library |
collection |
Institutional Repository |
continent |
Asia |
country |
Malaysia |
content_provider |
Universiti Utara Malaysia |
content_source |
UUM Electronic Theses |
url_provider |
http://etd.uum.edu.my/ |
language |
English English |
topic |
QA76 Computer software |
spellingShingle |
QA76 Computer software Srour, Ayman I. H. Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
description |
The Keystroke Level Model (KLM) has been utilized to predict the user behaviors and activities with desktop system. Recently, the mobile device application designers could use updated KLM model to predict the consumed time while users use mobile devices, but when designers use this
method to evaluate the text entry they still face some difficulties with the calculation of long equations, due to multi-tap technology. This study proposes new KLM operators to facilitate the time calculation process for text entry using traditional mobile keypad. Updated KLM operators are used to predict the user behavior in interacting with mobile devices in general and text entry in specific. The expected results contribute in estimating the consumed time accurately. |
format |
Thesis |
author |
Srour, Ayman I. H. |
author_facet |
Srour, Ayman I. H. |
author_sort |
Srour, Ayman I. H. |
title |
Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
title_short |
Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
title_full |
Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
title_fullStr |
Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
title_full_unstemmed |
Multi-Tap Mobile Phone Text Entry : Key-Press Operators For Keystroke Level Model |
title_sort |
multi-tap mobile phone text entry : key-press operators for keystroke level model |
publishDate |
2008 |
url |
http://etd.uum.edu.my/765/1/Ayman_I._H._Srour.pdf http://etd.uum.edu.my/765/2/Ayman_I._H._Srour.pdf http://etd.uum.edu.my/765/ |
_version_ |
1644276259626156032 |
score |
13.154949 |