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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Kitti Puritat | en_US |
dc.contributor.author | Manatchai Thatu | en_US |
dc.contributor.author | Pradorn Sureephong | en_US |
dc.date.accessioned | 2018-09-05T03:28:23Z | - |
dc.date.available | 2018-09-05T03:28:23Z | - |
dc.date.issued | 2017-04-19 | en_US |
dc.identifier.other | 2-s2.0-85019177983 | en_US |
dc.identifier.other | 10.1109/ICDAMT.2017.7904956 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85019177983&origin=inward | en_US |
dc.identifier.uri | http://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.subject | Arts and Humanities | en_US |
dc.subject | Computer Science | en_US |
dc.title | Enhancing Assistive Technology by the modification of the Thai word prediction application to improve the usability of students with learning disabilities | en_US |
dc.type | Conference Proceeding | en_US |
article.title.sourcetitle | 2nd Joint International Conference on Digital Arts, Media and Technology 2017: Digital Economy for Sustainable Growth, ICDAMT 2017 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
article.stream.affiliations | Mae Fah Luang University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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