Exploring the use of AI-Writing Assistant for Foreign Language Learners: A Mixed-Methods Study in the Saudi EFL Context
Keywords:
identity, sign, literary semiotics, Trauma, posttraumatic stress disorder, Professional development, Contract Faculty, Recognition Disparities, Job Security, Teaching Load., ChatGPT, AI-based writing assistant, learner perceptions, Saudi EFL context, automated feedbackAbstract
The rapid growth of AI writing assistants has changed language learning, but there are still gaps in understanding how learners use these tools effectively and perceive feedback from them to enhance their learning skills. This thesis investigates language learners’ interactions with an AI writing assistant called “Type,” identifying prompt types and understanding their perceptions for educational purposes. It is a mixed-methods study examining the interaction between English as a Foreign Language (EFL) learners and “Type.” Data was collected from 27 male university learners in Saudi Arabia who used “Type” for writing tasks, with pre- and post-surveys assessing their experiences with AI-assisted writing. Findings identified two main themes: anticipated and unexpected interactions. The study explores the types of prompts used, including style, grammar, and word count prompts. While most participants express satisfaction with the tool’s ability to improve writing skills, the study suggests that future research should expand the sample size and examine the level of proficiency learners have with AI tools. It is crucial to identify the specific errors learners make and analyze the limitations of each AI tool in the learning process.
References
J. S. Barrot (2023) Using automated written corrective feedback in the writing classrooms: Effects on L2 writing accuracy. 36(4), 584–607. https://doi.org/10.1080/09588221.2021.1936071
C. Andrade (2021) The inconvenient truth about convenience and purposive samples. 43(1), 86–88. https://doi.org/10.1177/0253717620977000
J. Bitchener, S. Young, D. Cameron (2005) The effect of different types of corrective feedback on ESL student writing. 14(3), 191–205. https://doi.org/10.1016/j.jslw.2005.08.001
J. Brooke (1996) SUS: A 'quick and dirty' usability scale. 189–194.
T. S. Chang, Y. Li, H. W. Huang, B. Whitfield (2021) Exploring EFL students' writing performance and their acceptance of AI-based automated writing feedback. 31–35. https://doi.org/10.1145/3459043.3459065
J. W. Creswell, J. D. Creswell (2018) Research design: Qualitative, quantitative, and mixed methods approaches.
R. A. Ellis, P. Goodyear, R. A. Calvo, M. Prosser (2008) Engineering students' conceptions of and approaches to learning through discussions in face-to-face and online contexts. 18(3), 267–295.
R. A. Ellis, A. M. Bliuc (2019) Exploring new elements of the student approaches to learning framework: The role of online learning technologies in student learning. 20(1), 11–24. https://doi.org/10.1177/1469787417721384
D. R. Garrison, J. B. Arbaugh (2007) Researching the community of inquiry framework: Review, issues, and future directions. 10(3), 157–172. https://doi.org/10.1016/j.iheduc.2007.04.001
D. R. Garrison, T. Anderson, W. Archer (2010) The first decade of the community of inquiry framework: A retrospective. 13(1–2), 5–9. https://doi.org/10.1016/j.iheduc.2009.10.003
M. A. Ghufron, F. Rosyida (2018) The role of Grammarly in assessing English as a Foreign Language (EFL) writing. 12(4), 395–403. https://doi.org/10.21512/lc.v12i4.4582
R. Jiang (2022) How does artificial intelligence empower EFL teaching and learning nowadays? A review on artificial intelligence in the EFL context. 13. https://doi.org/10.3389/fpsyg.2022.1049401
K. C. A. Khanzode, R. D. Sarode (2020) Advantages and disadvantages of artificial intelligence and machine learning: A literature review. 9(1), 21–30. https://iaeme.com/MasterAdmin/Journal_uploads/IJLIS/VOLUME_9_ISSUE_1/IJLIS_09_01_004.pdfIAEME+1IAEME+1
S. Link, M. Mehrzad, M. Rahimi (2020) Impact of automated writing evaluation on teacher feedback, student revision, and writing improvement. 605–634. https://doi.org/10.1080/09588221.2020.1743323
L. Lomicka (2020) Creating and sustaining virtual language communities. 53(2), 306–313. https://doi.org/10.1111/flan.12456
W. Marzuki, U. Widiati, D. Rusdin, Darwin, I. Indrawati (2023) The impact of AI writing tools on the content and organization of students' writing: EFL teachers' perspective. 10(2), 2236469. https://doi.org/10.1080/2331186X.2023.2236469
F. Meunier, M. Pikhart, B. Klimova (2022) New perspectives of L2 acquisition related to human-computer interaction (HCI). 13. https://doi.org/10.3389/fpsyg.2022.1098208
F. Ouyang, P. Jiao (2021) Artificial intelligence in education: The three paradigms. 18, 1–13. https://doi.org/10.1186/s41239-021-00249-3
A. Qassemzadeh, H. Soleimani (2016) The impact of feedback provision by Grammarly software and teachers on learning passive structures by Iranian EFL learners. 6(9), 1884–1894. https://doi.org/10.17507/tpls.0609.20
E. Ruane, A. Birhane, A. Ventresque (2019) Conversational AI: Social and ethical considerations. 153–159. https://doi.org/10.1145/3306618.3314284
M. D. Şahin, G. Ozturk (2019) Mixed method research: Theoretical foundations, designs and its use in educational research. 6(2), 301–310. https://doi.org/10.33200/ijcer.599138
J. Saldaña (2012) The coding manual for qualitative researchers.
E. Smidt, M. H. Chau, E. Rinehimer, P. Leever (2021) Exploring engagement of users of Global Englishes in a community of inquiry. 98, 102477. https://doi.org/10.1016/j.system.2021.102477
P. Thompson (2013) The digital natives as learners: Technology use patterns and approaches to learning. 65, 12–33. https://doi.org/10.1016/j.compedu.2012.12.022
D. G. Tight (2017) Tool usage and effectiveness among L2 Spanish computer writers. 34(1), 1–18. https://doi.org/10.1558/cj.27615
The all-in-one AI writing assistant. https://type.ai/
S. P. T. Utami, R. Winarni (2023) Utilization of artificial intelligence technology in English language learning: A case study. 14(2), 456–462. https://doi.org/10.17507/jltr.1402.23
S. Wichadee (2013) Peer feedback on Facebook: The use of social networking websites to develop writing ability of undergraduate students. 14(4), 260–270. https://doi.org/10.17718/tojde.34338
D. Yan (2023) Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. 28(11), 13943–13967. https://doi.org/10.1007/s10639-023-11752-5
R. Yılmaz (2020) Enhancing community of inquiry and reflective thinking skills of undergraduates through using learning analytics-based process feedback. 36(6), 909–921. https://doi.org/10.1111/jcal.12446
Downloads
Published
Issue
Section
License
Copyright (c) 2025 Authors and Global Journals Private Limited

This work is licensed under a Creative Commons Attribution 4.0 International License.
