Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/25295
Title: Investigation of Multiple Recognitions Used for EFL Writing in Authentic Contexts
Authors: Hwang, WY
Nguyen, VG
Chin, CC
Purba, SWD
Ghinea, G
Keywords: EFL writing;Recognition technology;Multimedia learning;Adaptive technologies
Issue Date: 26-Aug-2022
Publisher: Springer
Citation: Hwang, WY., Nguyen, VG., Chin, CC., Purba, S.W.D., Ghinea, G. (2022). Investigation of Multiple Recognitions Used for EFL Writing in Authentic Contexts. In: Huang, YM., Cheng, SC., Barroso, J., Sandnes, F.E. (eds) Innovative Technologies and Learning. ICITL 2022. Lecture Notes in Computer Science, vol 13449. https://doi.org/10.1007/978-3-031-15273-3_48
Abstract: Recognition technologies had been prevailing and widely used for EFL learning. We investigated the different recognitions used for EFL writing based on image-to-text, translated speech-to-text, and location-to-text recognitions – ITR, TSTR, and LTR. A quasi-experiment was implemented for 12 weeks in a vocational high school with experimental and control groups in two stages. Pre-test, posttests 1 and 2, questionnaires, and interviews were conducted and analyzed. Experimental learners, who wrote writing based on ITR and TSTR, outperformed control learners who wrote that based on TSTR only. Also, the experimental learners, who wore writing based on ITR, TSTR, and LTR, outperformed the control learners who wrote that based on ITR and TSTR. Particularly, LTR was beneficial for identifying controlling ideas and addressing the writing topics. ITR was beneficial for brainstorming and generating more ideas. TSTR was beneficial for yielding and transferring writing contents into words. The multiple recognitions were beneficial for most EFL writers, especially for low-ability language writers. Most writers were interested in describing based on authentic context learning. However, they complained about the low accuracy of LTR and TSTR and the difficulty of ITR texts when writing. Accordingly, the LTR database with various categories of places, the generation of ITR based on the language abilities of learners, and the higher accuracy of TSTR should be strictly considered when applying multiple recognitions for EFL writing.
URI: http://bura.brunel.ac.uk/handle/2438/25295
DOI: http://dx.doi.org/10.1007/978-3-031-15273-3_48
ISBN: 9783031152726
9783031152733
ISSN: 0302-9743
Appears in Collections:Dept of Computer Science Research Papers

Files in This Item:
File Description SizeFormat 
FullText.pdf601.95 kBAdobe PDFView/Open


Items in BURA are protected by copyright, with all rights reserved, unless otherwise indicated.