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DC Field | Value | Language |
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dc.contributor.author | Hwang, WY | - |
dc.contributor.author | Nguyen, VG | - |
dc.contributor.author | Chin, CC | - |
dc.contributor.author | Purba, SWD | - |
dc.contributor.author | Ghinea, G | - |
dc.date.accessioned | 2022-10-10T11:22:56Z | - |
dc.date.available | 2022-01-01 | - |
dc.date.available | 2022-10-10T11:22:56Z | - |
dc.date.issued | 2022-08-26 | - |
dc.identifier.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 | en_US |
dc.identifier.isbn | 9783031152726 | - |
dc.identifier.isbn | 9783031152733 | - |
dc.identifier.issn | 0302-9743 | - |
dc.identifier.uri | http://bura.brunel.ac.uk/handle/2438/25295 | - |
dc.description.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. | en_US |
dc.format.extent | 433 - 443 | - |
dc.publisher | Springer | en_US |
dc.subject | EFL writing | en_US |
dc.subject | Recognition technology | en_US |
dc.subject | Multimedia learning | en_US |
dc.subject | Adaptive technologies | en_US |
dc.title | Investigation of Multiple Recognitions Used for EFL Writing in Authentic Contexts | en_US |
dc.type | Conference Paper | en_US |
dc.identifier.doi | http://dx.doi.org/10.1007/978-3-031-15273-3_48 | - |
dc.relation.isPartOf | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) | - |
pubs.publication-status | Published | - |
pubs.volume | 13449 LNCS | - |
dc.identifier.eissn | 1611-3349 | - |
Appears in Collections: | Dept of Computer Science Research Papers |
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FullText.pdf | 601.95 kB | Adobe PDF | View/Open |
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