TY - GEN
T1 - The integration of multiple recognition technologies and artificial intelligence to facilitate EFL writing in authentic contexts
AU - Hwang, Wu Yuin
AU - Nurtantyana, Rio
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - English writing is a big challenge for the English as Foreign Language (EFL) learners due to the lack the lexical resources to inspire them for writing. However, we developed the mobile app, namely Smart UEnglish with the smart mechanisms by integrating multiple recognition technologies and artificial intelligence (AI) to help learners practice meaningful English writing in authentic contexts. Through the smart mechanisms like the integration of speech-to-text (STR), image-to-text recognition (ITR), and generative-AI, the learners could receive not only lexical resources but also sample sentences generated by AI (AI-GS) to inspire them to make meaningful writing. A total of 71 undergraduate students from two classes were assigned to two groups. The experimental group (EG) learns with Smart UEnglish including ITR, STR, and AI-GS. Meanwhile, the control group (CG) learns with ITR and STR only. The mix-method was used to analyze the study deeply. The results found that the EG outperformed the CG in the posttest. The ITR-generated texts as input for AI-GS could inspire the learners by giving the sample sentences before they write the essay. The use of ITR is the predictive variable in the post-test. In addition, the learners in EG have high positive perceptions towards Smart UEnglish. Hence, the integration of multiple recognition technologies and AI in the Smart UEnglish could facilitate EFL learners to learn meaningful writing in authentic contexts.
AB - English writing is a big challenge for the English as Foreign Language (EFL) learners due to the lack the lexical resources to inspire them for writing. However, we developed the mobile app, namely Smart UEnglish with the smart mechanisms by integrating multiple recognition technologies and artificial intelligence (AI) to help learners practice meaningful English writing in authentic contexts. Through the smart mechanisms like the integration of speech-to-text (STR), image-to-text recognition (ITR), and generative-AI, the learners could receive not only lexical resources but also sample sentences generated by AI (AI-GS) to inspire them to make meaningful writing. A total of 71 undergraduate students from two classes were assigned to two groups. The experimental group (EG) learns with Smart UEnglish including ITR, STR, and AI-GS. Meanwhile, the control group (CG) learns with ITR and STR only. The mix-method was used to analyze the study deeply. The results found that the EG outperformed the CG in the posttest. The ITR-generated texts as input for AI-GS could inspire the learners by giving the sample sentences before they write the essay. The use of ITR is the predictive variable in the post-test. In addition, the learners in EG have high positive perceptions towards Smart UEnglish. Hence, the integration of multiple recognition technologies and AI in the Smart UEnglish could facilitate EFL learners to learn meaningful writing in authentic contexts.
KW - EFL writing
KW - artificial intelligence
KW - image-to-text recognition
KW - recognition technologies
KW - speech-to-text recognition
UR - http://www.scopus.com/inward/record.url?scp=85151707037&partnerID=8YFLogxK
U2 - 10.1109/InCIT56086.2022.10067490
DO - 10.1109/InCIT56086.2022.10067490
M3 - 會議論文篇章
AN - SCOPUS:85151707037
T3 - 6th International Conference on Information Technology, InCIT 2022
SP - 379
EP - 383
BT - 6th International Conference on Information Technology, InCIT 2022
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 6th International Conference on Information Technology, InCIT 2022
Y2 - 10 November 2022 through 11 November 2022
ER -