Investigation of Multiple Recognitions Used for EFL Writing in Authentic Contexts

Wu Yuin Hwang, Van Giap Nguyen, Chi Chieh Chin, Siska Wati Dewi Purba, George Ghinea

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

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.

原文???core.languages.en_GB???
主出版物標題Innovative Technologies and Learning - 5th International Conference, ICITL 2022, Proceedings
編輯Yueh-Min Huang, Shu-Chen Cheng, João Barroso, Frode Eika Sandnes
發行者Springer Science and Business Media Deutschland GmbH
頁面433-443
頁數11
ISBN(列印)9783031152726
DOIs
出版狀態已出版 - 2022
事件5th International Conference on Innovative Technologies and Learning, ICITL 2022 - Virtual, Online
持續時間: 29 8月 202231 8月 2022

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
13449 LNCS
ISSN(列印)0302-9743
ISSN(電子)1611-3349

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???event.eventtypes.event.conference???5th International Conference on Innovative Technologies and Learning, ICITL 2022
城市Virtual, Online
期間29/08/2231/08/22

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