Abstract
Most studies of English as a Foreign Language (EFL) writing usually used grammar checking to help EFL learners to check writing errors. However, it is not enough since EFL learners have to learn how to create more meaningful content, particularly using their surroundings in authentic contexts. Therefore, we develop one app, Ubiquitous English (UEnglish), with recognition technology, particularly Image-to-Text Recognition (ITR) texts to provide the vocabulary and description from authentic pictures, and generative-AI that can generate meaningful questions and clarifications to trigger EFL learners to write more. In addition, EFL learners need to answer the question from generative-AI before they receive the clarification. Hence, we proposed a Smart Questioning-Answering-Clarification (QAC) mechanism to help EFL writing. A total of 35 participants were assigned into two groups, experimental groups (EG) with 19 learners and control groups (CG) with 16 learners with/without Smart QAC mechanism support, respectively. In this study, the quasi-experiment was conducted over five weeks and we used quantitative analysis methods. The results revealed that the EG with ITR-texts and Smart QAC had a significant difference with CG in the learning behaviors and post-test. Furthermore, EG could write more meaningful words in the assignments. Therefore, the Smart QAC mechanism could facilitate EFL learners to enhance their EFL writing in authentic contexts.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Hwang, W.-Y., Nguyen, V.-G., Purba, S.W.D.: Systematic survey of anything-to-text recognition and constructing its framework in language learning. Educ. Inf. Technol. 27(9), 12273–12299 (2022)
Hwang, W.-Y., Nurtantyana, R., Purba, S.W.D., Hariyanti, U., Indrihapsari, Y., Surjono, H.D.: AI and recognition technologies to facilitate English as Foreign language writing for supporting personalization and contextualization in authentic contexts. J. Educ. Comput. Res. (2023)
Shadiev, R., Wu, T.-T., Huang, Y.-M.: Using image-to-text recognition technology to facilitate vocabulary acquisition in authentic contexts. ReCALL 32(2), 195–212 (2020)
Gayed, J.M., Carlon, M.K.J., Oriola, A.M., Cross, J.S.: Exploring an AI-based writing assistant’s impact on English language learners. Comput. Educ.: Artif. Intell. 3 (2022)
Shadiev, R., Hwang, W.-Y., Chen, N.-S., Huang, Y.-M.: Review of speech-to-text recognition technology for enhancing learning. Educ. Technol. Soc. 17(4), 65–84 (2014)
Nguyen, T.-H., Hwang, W.-Y., Pham, X.-L., Pham, T.: Self-experienced storytelling in an authentic context to facilitate EFL writing. Comput. Assist. Lang. Learn. 35(4), 666 (2022)
Hwang, W.-Y., Nurtantyana, R.: The integration of multiple recognition technologies and artificial intelligence to facilitate EFL writing in authentic contexts. In: 6th International Conference on Information Technology (InCIT), Thailand, pp. 379–383. IEEE (2022)
Hwang, W.-Y., Nurtantyana, R.: X-education: education of all things with ai and edge computing -one case study for EFL learning. Sustainability 14(19), 12533 (2022)
Tofade, T., Elsner, J., Haines, S.T.: Best practice strategies for effective use of questions as a teaching tool. Am. J. Pharm. Educ. 77(7), 155 (2013)
Hwang, W.-Y., Nurtantyana, R., Hariyanti, U.: Collaboration and interaction with smart mechanisms in flipped classrooms. Data Technol. Appl. (2023)
Etemadzadeh, A., Seifi, S., Far, H.R.: The role of questioning technique in developing thinking skills: the ongoing effect on writing skill. Procedia – Soc. Behav. Sci. 1024–1031 (2013)
Acknowledgments
This work was partly supported by National Science and Technology Council, Taiwan under grant NSTC110-2511-H-035-002-MY2, NSTC 111-2410-H-008-061-MY3, and NSTC109-2511-H-008-009-MY3.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this paper
Cite this paper
Hwang, WY., Nurtantyana, R., Lai, YF., Chiang, IC.N., Ghenia, G., Tsai, MH.M. (2023). The Combination of Recognition Technology and Artificial Intelligence for Questioning and Clarification Mechanisms to Facilitate Meaningful EFL Writing in Authentic Contexts. In: Huang, YM., Rocha, T. (eds) Innovative Technologies and Learning. ICITL 2023. Lecture Notes in Computer Science, vol 14099. Springer, Cham. https://doi.org/10.1007/978-3-031-40113-8_7
Download citation
DOI: https://doi.org/10.1007/978-3-031-40113-8_7
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-40112-1
Online ISBN: 978-3-031-40113-8
eBook Packages: Computer ScienceComputer Science (R0)