Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/56646
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dc.contributor.authorKitti Puritaten_US
dc.contributor.authorManatchai Thatuen_US
dc.contributor.authorPradorn Sureephongen_US
dc.date.accessioned2018-09-05T03:28:23Z-
dc.date.available2018-09-05T03:28:23Z-
dc.date.issued2017-04-19en_US
dc.identifier.other2-s2.0-85019177983en_US
dc.identifier.other10.1109/ICDAMT.2017.7904956en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019177983&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/56646-
dc.description.abstract© 2017 IEEE. This research shows the results of the modification of the Thai word prediction from NECTEC to support the effectiveness of word processing tools in improving the literacy skills and usability of the original Thai word prediction program for students with learning disabilities in grades 4-12. The entry strategies of 2 groups of 40 students with learning disabilities were compared. The original group used Thai word prediction app and the modified group used our program. We improved the original program by adding functions by which the student can select the suitable function to predict the word individually according to the user's disability level. The students could select alterative input modes of prediction, like predicting the word by sound, photo or animation instead of only by typing on the keyboard. The investigations of our research showed that our added functions can improve the usability in terms of the overall speed. Users of the modified version could predict the words 20 percent faster than users of the original version.en_US
dc.subjectArts and Humanitiesen_US
dc.subjectComputer Scienceen_US
dc.titleEnhancing Assistive Technology by the modification of the Thai word prediction application to improve the usability of students with learning disabilitiesen_US
dc.typeConference Proceedingen_US
article.title.sourcetitle2nd Joint International Conference on Digital Arts, Media and Technology 2017: Digital Economy for Sustainable Growth, ICDAMT 2017en_US
article.stream.affiliationsChiang Mai Universityen_US
article.stream.affiliationsMae Fah Luang Universityen_US
Appears in Collections:CMUL: Journal Articles

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