TY - GEN
T1 - Investigation of Multiple Recognitions Used for EFL Writing in Authentic Contexts
AU - Hwang, Wu Yuin
AU - Nguyen, Van Giap
AU - Chin, Chi Chieh
AU - Purba, Siska Wati Dewi
AU - Ghinea, George
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - 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.
AB - 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.
KW - Adaptive technologies
KW - EFL writing
KW - Multimedia learning
KW - Recognition technology
UR - http://www.scopus.com/inward/record.url?scp=85137973165&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-15273-3_48
DO - 10.1007/978-3-031-15273-3_48
M3 - 會議論文篇章
AN - SCOPUS:85137973165
SN - 9783031152726
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 433
EP - 443
BT - Innovative Technologies and Learning - 5th International Conference, ICITL 2022, Proceedings
A2 - Huang, Yueh-Min
A2 - Cheng, Shu-Chen
A2 - Barroso, João
A2 - Sandnes, Frode Eika
PB - Springer Science and Business Media Deutschland GmbH
T2 - 5th International Conference on Innovative Technologies and Learning, ICITL 2022
Y2 - 29 August 2022 through 31 August 2022
ER -