Please use this identifier to cite or link to this item: http://hdl.handle.net/1822/43340

TitleLearning new words and spelling with autocorrections
Author(s)Arif, Ahmed Sabbir
Sylla, Cristina Maria Santos Moreira Silva
Mazalek, Ali
KeywordsChildren
Predictive keyboard
Color-coded autocorrect
Autocorrection
Spelling
Child
prediction
Issue date6-Nov-2016
PublisherACM
CitationArif, A, Sylla, C., Mazalek, A. (2016). Learning New Words and Spelling with Autocorrections. In Proceedings of the ACM, International Conference on Interactive Surfaces and Spaces, ISS’16, Niaga Falls, Canada, Nov, 6-9. New York, NY: ACM Press. doi> http://dx.doi.org/10.1145/2992154.2996790.
Abstract(s)We present a novel color-coded feedback method that highlights the types of corrections made by autocorrections. We then present results of a longitudinal user study with 7-8-year-old children that compared the new method with the conventional autocorrection feedback method, in terms of leaning new words and spelling. Results suggested that the new method better accommodates learning new words. Interestingly, learning was observed with the conventional feedback method as well, demanding further investigation into whether predictive methods are truly a barrier to learning new words and spelling.
TypeConference paper
URIhttp://hdl.handle.net/1822/43340
ISBN978-1-4503-4248-3
DOI10.1145/2992154.2996790
Publisher versionhttp://dl.acm.org/citation.cfm?doid=2992154.2996790
Peer-Reviewedyes
AccessOpen access
Appears in Collections:CIEC - Textos em atas

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