Incorporating ChatGPT as an automated written corrective feedback tool into L2 writing class

Authors

  • Yifeng Zhang The University of Hong Kong

DOI:

https://doi.org/10.54475/jlt.2024.024

Keywords:

L2 writing, written corrective feedback, automated written corrective feedback, ChatGPT, automated writing evaluation tools

Abstract

This review focuses on the use of automated written corrective feedback (AWCF) tools, particularly ChatGPT, in second language (L2) writing instruction. Writing is essential but challenging for L2 learners, and feedback plays a crucial role in enhancing writing skills. However, traditional teacher-provided written corrective feedback (WCF) faces challenges such as time constraints, cognitive overload, and inconsistency, especially in large classes. AWCF tools like Grammarly, Criterion, and ChatGPT help overcome these limitations by providing immediate and comprehensive feedback. The review begins by discussing the role of WCF in L2 writing, while highlighting the challenges associated with traditional feedback provision methods. It then explores the benefits and limitations of AWCF tools based on existing studies, noting their ability to offer instant feedback, reduce teachers’ workload, and motivate learners. Focusing on ChatGPT, the review highlights its ability to generate contextually appropriate and personalized feedback. ChatGPT offers several advantages, including promoting learner autonomy, enhancing feedback literacy, and improving writing quality by providing immediate corrections and suggestions. Learners have also shown positive perceptions of ChatGPT’s feedback in addressing grammatical errors and improving writing complexity.

Author Biography

  • Yifeng Zhang, The University of Hong Kong

    Yifeng Zhang is currently pursuing a master’s degree in the field of applied linguistics at The University of Hong Kong. He holds a Bachelor of Arts in English Education from Shanghai Normal University. His research interests lie in language testing, second language acquisition, and AI-assisted language learning, reflecting his passion for advancing technology-enhanced language education. Yifeng has authored some educational materials, including the forthcoming Shanghai College Entrance Examination English Vocabulary Handbook, and led impactful research projects, such as exploring multilingual competence among students in Shanghai.
    Email: zhangyifeng_1998@163.com

References

AlAfnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). ChatGPT as an educational tool: Opportunities, challenges, and recommendations for communication, business writing, and composition courses. Journal of Artificial Intelligence and Technology, 3(2), Article 2. https://doi.org/10.37965/jait.2023.0184 DOI: https://doi.org/10.37965/jait.2023.0184

Attali, Y., & Burstein, J. (2006). Automated essay scoring with e-rater® V.2. The Journal of Technology, Learning and Assessment, 4(3).

Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, 100745. DOI: https://doi.org/10.1016/j.asw.2023.100745

Bitchener, J. (2008). Evidence in support of written corrective feedback. Journal of second language writing, 17(2), 102-118. DOI: https://doi.org/10.1016/j.jslw.2007.11.004

Bitchener, J., & Ferris, D.R. (2012). Written corrective feedback in second language acquisition and writing. Routledge. DOI: https://doi.org/10.4324/9780203832400

Bitchener, J. and Knoch, U. (2008) The value of written corrective feedback for migrant and international students. Language Teaching Research, 12, 409-431. http://dx.doi.org/10.1177/1362168808089924 DOI: https://doi.org/10.1177/1362168808089924

Bitchener, J., & Knoch, U. (2010). Raising the linguistic accuracy level of advanced L2 writers with written corrective feedback. Journal of Second Language Writing, 19, 207-217. https://doi.org/10.1016/j.jslw.2010.10.002 DOI: https://doi.org/10.1016/j.jslw.2010.10.002

Bloxham, S., & Boyd, P. (2008). Developing effective assessment in Higher Education: A practical guide (repr). Open University Press.

Bonk, C. J., & Graham, C. R. (2012). The handbook of blended learning: Global perspectives, local designs. John Wiley & Sons.

Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., ... & Amodei, D. (2020). Language models are few-shot learners. Advances in Neural Information Processing Systems, 33, 1877-1901.

Cavaleri, M., Kawaguchi, S., Di Biase, B., & Power, C. (2019). How recorded audio-visual feedback can improve academic language support. Journal of University Teaching & Learning Practice, 16(4). DOI: https://doi.org/10.53761/1.16.4.6

Chandler, J. (2003). The efficacy of various kinds of error feedback for improvement in the accuracy and fluency of L2 student writing. Journal of Second Language Writing, 12(3), 267–296. DOI: https://doi.org/10.1016/S1060-3743(03)00038-9

Cao, Z. (2021). Improving young learners’ L2 writing accuracy with written corrective feedback: A case study. English Teaching & Learning, 45(4), 375–396. https://doi.org/10.1007/s42321-020-00071-1 DOI: https://doi.org/10.1007/s42321-020-00071-1

Carless, D., & Boud, D. (2018). The development of student feedback literacy: Enabling uptake of feedback. Assessment & Evaluation in Higher Education, 43(8), 1315–1325. https://doi.org/10.1080/02602938.2018.1463354 DOI: https://doi.org/10.1080/02602938.2018.1463354

Cen, Y., & Zheng, Y. (2024). The motivational aspect of feedback: A meta-analysis on the effect of different feedback practices on L2 learners’ writing motivation. Assessing Writing, 59, 100802. https://doi.org/10.1016/j.asw.2023.100802 DOI: https://doi.org/10.1016/j.asw.2023.100802

Craven, L. (2023). The effects of different types of unfocused corrective feedback on complexity, accuracy and fluency in L2 English academic writing (Doctoral dissertation, University of Essex).

Crossley, S. A. (2020). Linguistic features in writing quality and development: An overview. Journal of Writing Research, 11(3), 415-443. DOI: https://doi.org/10.17239/jowr-2020.11.03.01

Cumming, A. (2002). Assessing L2 writing: Alternative constructs and ethical dilemmas. Assessing writing, 8(2), 73-83. DOI: https://doi.org/10.1016/S1075-2935(02)00047-8

Duncan, N. (2007). ‘Feed-forward’: Improving students’ use of tutors’ comments. Assessment & Evaluation in Higher Education, 32(3), 271-283. DOI: https://doi.org/10.1080/02602930600896498

Ebadi, S., & Amini, A. (2022). Examining the roles of social presence and human-likeness on Iranian EFL learners’ motivation using artificial intelligence technology: A case of CSIEC chatbot. Interactive Learning Environments, 0(0), 1–19 https://doi.org/10.1080/10494820.2022.2096638 DOI: https://doi.org/10.1080/10494820.2022.2096638

Ellis, R. (2009). Corrective feedback and teacher development. L2 Journal, 1, 3-18. https://doi.org/10.5070/L2.V1I1.9054 DOI: https://doi.org/10.5070/L2.V1I1.9054

Evans, N. W., Hartshorn, K. J., & Tuioti, E. A. (2010). Written corrective feedback: The practitioners’ perspective. International Journal of English Studies, 10(2), 47-77. DOI: https://doi.org/10.6018/ijes/2010/2/119191

Fan, N. (2023). Exploring the effects of automated written corrective feedback on EFL students’ writing quality: A mixed-methods study. SAGE Open, 13(2), 21582440231181296. DOI: https://doi.org/10.1177/21582440231181296

Farida, A. N., & Rosyidi, M. I. (2019). Students’ writing quality: Its coherence and cohesion. Language Circle: Journal of Language and Literature, 14(1), 121– 129. https://doi.org/10.15294/lc.v14i1.21505 DOI: https://doi.org/10.15294/lc.v14i1.21505

Ferris, D. R. (1997). The influence of teacher commentary on student revision. TESOL Quarterly, 31(2), 315-339. DOI: https://doi.org/10.2307/3588049

Ferris, D. R. (2003). Response to student writing: Implications for second language students. Lawrence Erlbaum Associates. DOI: https://doi.org/10.4324/9781410607201

Ferris, D. R. (2004). The “grammar correction” debate in L2 writing: Where are we, and where do we go from here? (and what do we do in the meantime…?). Journal of Second Language Writing, 13(1), 49-62. DOI: https://doi.org/10.1016/j.jslw.2004.04.005

Ferris, D. (2011). Treatment of error in second language student writing. University of Michigan Press. DOI: https://doi.org/10.3998/mpub.2173290

Ferris, D., & Roberts, B. (2001). Error feedback in the L2 writing classes: How explicit does it need to be? Journal of Second Language Writing, 10, 161-184. https://doi.org/10.1016/S1060-3743(01)00039-X DOI: https://doi.org/10.1016/S1060-3743(01)00039-X

Fu, Q. K., Zou, D., Xie, H., & Cheng, G. (2024). A review of AWE feedback: Types, learning outcomes, and implications. Computer Assisted Language Learning, 37(1-2), 179-221. DOI: https://doi.org/10.1080/09588221.2022.2033787

Ghafouri, M., Hassaskhah, J., & Mahdavi-Zafarghandi, A. (2024). From virtual assistant to writing mentor: Exploring the impact of a ChatGPT-based writing instruction protocol on EFL teachers’ self-efficacy and learners’ writing skill. Language Teaching Research, 13621688241239764. https://doi.org/10.1177/13621688241239764 DOI: https://doi.org/10.1177/13621688241239764

Goldstein, L. (2006). Feedback and revision in second language writing: Contextual, teacher, and student variables. Feedback in second language writing: Contexts and issues, 185-205. DOI: https://doi.org/10.1017/CBO9781139524742.012

Grammarly. (2024). How grammarly works. Retrieved from https://www.grammarly.com/how-grammarly-works

Gu, Y., & Johnson, R. K. (1996). Vocabulary learning strategies and language learning outcomes. Language Learning, 46(4), 643-679. DOI: https://doi.org/10.1111/j.1467-1770.1996.tb01355.x

Guo, Q., Feng, R., & Hua, Y. (2022). How effectively can EFL students use automated written corrective feedback (AWCF) in research writing?. Computer Assisted Language Learning, 35(9), 2312-2331. DOI: https://doi.org/10.1080/09588221.2021.1879161

Guo, K., & Wang, D. (2023). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feedback in EFL writing. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12146-0 DOI: https://doi.org/10.1007/s10639-023-12146-0

Han, T., & Sari, E. (2024). An investigation on the use of automated feedback in Turkish EFL students’ writing classes. Computer Assisted Language Learning, 37(4), 961–985. https://doi.org/10.1080/09588221.2022.2067179 DOI: https://doi.org/10.1080/09588221.2022.2067179

Hassanzadeh, M., & Fotoohnejad, S. (2021). Implementing an automated feedback program for a Foreign Language writing course: A learner‐centric study: Implementing an AWE tool in a L2 class. Journal of Computer Assisted Learning, 37(5), 1494-1507. DOI: https://doi.org/10.1111/jcal.12587

Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487 DOI: https://doi.org/10.3102/003465430298487

Huang, W., Hew, K. F., & Fryer, L. K. (2022). Chatbots for language learning—Are they really useful? A systematic review of chatbot-supported language learning. Journal of Computer Assisted Learning, 38(1), 237–257. https://doi.org/10.1111/jcal.12610 DOI: https://doi.org/10.1111/jcal.12610

Hyland, F. (1998). The impact of teacher written feedback on individual writers. Journal of Second Language Writing, 7(3), 255-286. DOI: https://doi.org/10.1016/S1060-3743(98)90017-0

Hyland, F., & Hyland, K. (2001). Sugaring the pill: Praise and criticism in written feedback. Journal of Second Language Writing, 10(3), 185-212. DOI: https://doi.org/10.1016/S1060-3743(01)00038-8

Hyland, K. (2016). Methods and methodologies in second language writing research. System, 59, 116-125. DOI: https://doi.org/10.1016/j.system.2016.05.002

Hyland, K., & Hyland, F. (2006). Feedback on second language students’ writing. Language Teaching, 39(2), 83-101. DOI: https://doi.org/10.1017/S0261444806003399

Innaci, D. L., & Jona, P. H. (2024). AI in second language learning: Leveraging automated writing assistance tools for improving learners’ writing task assessment. Jamal Academic Research Journal: An interdisciplinary, 5(1).

Jeon, J., & Lee, S. (2023). Large language models in education: A focus on the complementary relationship between human teachers and ChatGPT. Education and Information Technologies, 28, 15873–15892. https://doi.org/10.1007/s10639-023-11834-1 DOI: https://doi.org/10.1007/s10639-023-11834-1

Karunarathne, W., Selman, C., & Ryan, T. (2023). Evaluating student feedback literacies: A study using first-year business and economics students. Assessment & Evaluation in Higher Education, 1–14. https://doi.org/10.1080/02602938.2023.2267803 DOI: https://doi.org/10.1080/02602938.2023.2267803

Kasneci, E., Seßler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A. . . . Kuhn, J. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274 DOI: https://doi.org/10.1016/j.lindif.2023.102274

Kazemian, M., Irawan, L. A., & Haerazi, H. (2021). Developing metacognitive writing strategy to enhance writing skills viewed from prospective teachers’ critical thinking skills. Journal of Language and Literature Studies, 1(1), 14. DOI: https://doi.org/10.36312/jolls.v1i1.499

Kulik, J. A., & Fletcher, J. D. (2016). Effectiveness of intelligent tutoring systems: A meta-analytic review. Review of Educational Research, 86(1), 42-78. DOI: https://doi.org/10.3102/0034654315581420

Lating, A. Z. Y. (2022). The improvement of the students’ ability in writing procedure text using video recipe. Journal of Languages and Language Teaching, 10(3), 461. DOI: https://doi.org/10.33394/jollt.v10i3.5328

Lee, I. (2008). Student reactions to teacher feedback in two Hong Kong secondary classrooms. Journal of Second Language Writing, 17(3), 144-164. DOI: https://doi.org/10.1016/j.jslw.2007.12.001

Lee, I. (2017). Classroom writing assessment and feedback in L2 school contexts. Springer. DOI: https://doi.org/10.1007/978-981-10-3924-9

Lee, I., Karaca, M., & Inan, S. (2023). The development and validation of a scale on L2 writing teacher feedback literacy. Assessing Writing, 57, 100743. https://doi.org/10.1016/j.asw.2023.100743 DOI: https://doi.org/10.1016/j.asw.2023.100743

Lee, C., Wong, K., Cheung, W., & Lee, F. (2009). Web-based essay critiquing system and EFL students’ writing: A quantitative and qualitative investigation. Computer Assisted Language Learning, 22(1), 57–72. https://doi.org/10.1080/09588220802613807 DOI: https://doi.org/10.1080/09588220802613807

Li, J., Link, S., & Hegelheimer, V. (2015). Rethinking the role of automated writing evaluation (AWE) feedback in ESL writing instruction. Journal of Second Language Writing, 27, 1-18. DOI: https://doi.org/10.1016/j.jslw.2014.10.004

Li, R. (2023). Still a fallible tool? Revisiting effects of automated writing evaluation from activity theory perspective. British Journal of Educational Technology, 54(3), 773-789. DOI: https://doi.org/10.1111/bjet.13294

Li, X., Li, B., & Cho, S. J. (2023). Empowering Chinese language learners from low-income families to improve their Chinese writing with ChatGPT’s assistance afterschool. Languages, 8(4), 238–254. https://doi.org/10.3390/languages8040238 DOI: https://doi.org/10.3390/languages8040238

Liao, H. C. (2016). Using automated writing evaluation to reduce grammar errors in writing. ELT Journal, 70(3), 308–319. https://doi.org/10.1093/elt/ccv058 DOI: https://doi.org/10.1093/elt/ccv058

Little, T., Dawson, P., Boud, D., & Tai, J. (2024). Can students’ feedback literacy be improved? A scoping review of interventions. Assessment & Evaluation in Higher Education, 49(1), 39–52. https://doi.org/10.1080/02602938.2023.2177613 DOI: https://doi.org/10.1080/02602938.2023.2177613

Liu, Q., & Brown, D. (2015). Methodological synthesis of research on the effectiveness of corrective feedback in L2 writing. Journal of Second Language Writing, 30, 66-81. DOI: https://doi.org/10.1016/j.jslw.2015.08.011

Mizumoto, A., & Takeuchi, O. (2009). Examining the effectiveness of explicit instruction of vocabulary learning strategies with Japanese EFL university students. Language Teaching Research, 13(4), 425–449. https://doi.org/10.1177/1362168809341511 DOI: https://doi.org/10.1177/1362168809341511

Mohamed, A. M. (2024). Exploring the potential of an AI-based chatbot (ChatGPT) in enhancing English as a foreign language (EFL) teaching: Perceptions of EFL faculty members. Education and Information Technologies, 29, 3195–3217. https://doi.org/10.1007/s10639-023-11917-z DOI: https://doi.org/10.1007/s10639-023-11917-z

Nation, I. S. P. (2009). Teaching ESL/EFL Reading and Writing. Routledge. DOI: https://doi.org/10.4324/9780203891643

Nugroho, A., Andriyanti, E., Widodo, P., & Mutiaraningrum, I. (2024). Students’ appraisals post-ChatGPT use: Students’ narrative after using ChatGPT for writing. Innovations in Education and Teaching International, 1–13. https://doi.org/10.1080/14703297.2024.2319184 DOI: https://doi.org/10.1080/14703297.2024.2319184

OpenAI. (2022, November 30). ChatGPT: Optimizing language models for dialogue. OpenAI. https://openai.com/blog/chatgpt/

Popham, W. J. (2008). Transformative Assessment. ASCD.

Praphan, P. W., & Praphan, K. (2023). AI technologies in the ESL/EFL writing classroom: The villain or the champion? Journal of Second Language Writing, 62, 101072. https://doi.org/10.1016/j.jslw.2023.101072 DOI: https://doi.org/10.1016/j.jslw.2023.101072

Radford, A., Wu, J., Child, R., et al. (2019) Language Models Are Unsupervised Multitask Learners. OpenAI Blog, 1.

Ranalli, J. (2018). Automated written corrective feedback: How well can students make use of it?. Computer Assisted Language Learning, 31(7), 653-674. DOI: https://doi.org/10.1080/09588221.2018.1428994

Ray, P.P. (2023). ChatGPT: A comprehensive review on background, applications, key challenges, bias, ethics, limitations and future scope. Internet of Things and Cyber-Physical Systems, 3, 121–154. DOI: https://doi.org/10.1016/j.iotcps.2023.04.003

Reynolds, B. L., Kao, C.-W., & Huang, Y. (2021). Investigating the effects of perceived feedback source on second language writing performance: A quasi-experimental study. The Asia-Pacific Education Researcher, 30(6), 585–595. https://doi.org/10.1007/s40299-021-00597-3 DOI: https://doi.org/10.1007/s40299-021-00597-3

Roumeliotis, K. I., & Tselikas, N. D. (2023). ChatGPT and open-ai models: A preliminary review. Future Internet, 15(6), 192. DOI: https://doi.org/10.3390/fi15060192

Sadler, D. R. (1998) Formative assessment: Revisiting the territory, Assessment in Education, 5(1), 77–84. DOI: https://doi.org/10.1080/0969595980050104

Shang, H.-F. (2022). Exploring online peer feedback and automated corrective feedback on EFL writing performance. Interactive Learning Environments, 30(1), 4–16. https://doi.org/10.1080/10494820.2019.1629601 DOI: https://doi.org/10.1080/10494820.2019.1629601

Shermis, M. D., & Burstein, J. (Eds.). (2013). Handbook of automated essay evaluation: Current applications and new directions. Routledge/Taylor & Francis Group. DOI: https://doi.org/10.4324/9780203122761

Shintani, N., & Ellis, R. (2013). The comparative effect of direct written corrective feedback and metalinguistic explanation on learners’ explicit and implicit knowledge of the English indefinite article. Journal of second language writing, 22(3), 286-306. DOI: https://doi.org/10.1016/j.jslw.2013.03.011

Stevenson, M., & Phakiti, A. (2014). The effects of computer-generated feedback on the quality of writing. Assessing Writing, 19, 51-65. DOI: https://doi.org/10.1016/j.asw.2013.11.007

Storch, N., & Wigglesworth, G. (2010). Learners ‘processing, uptake, and retention of corrective feedback on writing: Case studies. Studies in Second Language Acquisition, 32(2), 303-334. DOI: https://doi.org/10.1017/S0272263109990532

Su, Y., Lin, Y., & Lai, C. (2023). Collaborating with ChatGPT in argumentative writing classrooms. Assessing Writing, 57, 100752. https://doi.org/10.1016/j.asw.2023.100752 DOI: https://doi.org/10.1016/j.asw.2023.100752

Sweller, J. (1988). Cognitive load during problem solving: Effects on learning. Cognitive Science, 12(2), 257–285. https://doi.org/10.1207/s15516709cog1202_4 DOI: https://doi.org/10.1016/0364-0213(88)90023-7

Tam, A. C. F. (2024). Interacting with ChatGPT for internal feedback and factors affecting feedback quality. Assessment & Evaluation in Higher Education, 1–17. https://doi.org/10.1080/02602938.2024.2374485 DOI: https://doi.org/10.1080/02602938.2024.2374485

Truscott, J. (1996) The Case against Grammar Correction in L2 Writing Classes. Language Learning, 46, 327-369. http://dx.doi.org/10.1111/j.1467-1770.1996.tb01238.x DOI: https://doi.org/10.1111/j.1467-1770.1996.tb01238.x

Tsao, J.-J. (2021). Effects of EFL learners’ L2 writing self-efficacy on engagement with written corrective feedback. The Asia-Pacific Education Researcher, 30(6), 575–584. https://doi.org/10.1007/s40299-021-00591-9 DOI: https://doi.org/10.1007/s40299-021-00591-9

Turnitin. (2024). Revision assistant. Retrieved from https://www.turnitin.com/products/revision-assistant

Van Beuningen, C. (2010). Corrective feedback in L2 writing: Theoretical Perspectives, Empirical Insights, and Future Directions. International Journal of English Studies, 10(2), 1–27. DOI: https://doi.org/10.6018/ijes/2010/2/119171

Van Beuningen, C. G., De Jong, N. H., & Kuiken, F. (2012). Evidence on the effectiveness of comprehensive error correction in second language writing. Language Learning, 62(1), 1–41. https://doi.org/10.1111/j.1467-9922.2011.00674.x DOI: https://doi.org/10.1111/j.1467-9922.2011.00674.x

VanLehn, K. (2011). The relative effectiveness of human tutoring, intelligent tutoring systems, and other tutoring systems. Educational Psychologist, 46(4), 197–221. https://doi.org/10.1080/00461520.2011.611369 DOI: https://doi.org/10.1080/00461520.2011.611369

Vaswani, A., Shazeer, N., Parmar, N., Uszkoreit, J., Jones, L., Gomez, A. N., ... & Polosukhin, I. (2017). Attention is all you need. In Advances in Neural Information Processing Systems (pp. 5998-6008).

Wang, Z., & Han, F. (2022). The effects of teacher feedback and automated feedback on cognitive and psychological aspects of foreign language writing: A mixed-methods research. Frontiers in Psychology, 13, 909802. https://doi.org/10.3389/fpsyg.2022.909802 DOI: https://doi.org/10.3389/fpsyg.2022.909802

Wenzlaf, K., & Spaeth, S. (2022). Smarter than humans? Validating how OpenAI’s ChatGPT model explains crowdfunding, Alternative Finance and Community Finance. SSRN Scholarly Paper. https://doi.org/10.2139/ssrn.4302443 DOI: https://doi.org/10.2139/ssrn.4302443

Wilson, J., & Czik, A. (2016). Automated essay evaluation software in English Language Arts classrooms: Effects on teacher feedback, student motivation, and writing quality. Computers & Education, 100, 94-109. DOI: https://doi.org/10.1016/j.compedu.2016.05.004

Wilson, J., Huang, Y., Palermo, C., Beard, G., & MacArthur, C. A. (2021). Automated feedback and automated scoring in the elementary grades: Usage, attitudes, and associations with writing outcomes in a districtwide implementation of MI Write. International Journal of Artificial Intelligence in Education, 31, 234–276. https://doi.org/10.1007/s40593-020-00236-w DOI: https://doi.org/10.1007/s40593-020-00236-w

Wilson, J., Palermo, C., & Wibowo, A. (2024). Elementary English learners’ engagement with automated feedback. Learning and Instruction, 91, 101890. https://doi.org/10.1016/j.learninstruc.2024.101890 DOI: https://doi.org/10.1016/j.learninstruc.2024.101890

Wilson, J., & Roscoe, R. D. (2020). Automated writing evaluation and feedback: Multiple metrics of efficacy. Journal of Educational Computing Research, 58(1), 87-125. DOI: https://doi.org/10.1177/0735633119830764

Yan, D. (2023). Impact of ChatGPT on learners in a L2 writing practicum: An exploratory investigation. Education and Information Technologies, 28(11), 13943-13967. DOI: https://doi.org/10.1007/s10639-023-11742-4

Yeadon, W., Inyang, O.-O., Mizouri, A., Peach, A., & Testrow, C. (2022). The death of the short-form physics essay in the coming AI revolution (arXiv:2212.11661). arXiv. https://doi.org/10.48550/arXiv.2212.11661 DOI: https://doi.org/10.1088/1361-6552/acc5cf

Zhai, X. (2022). ChatGPT user experience: Implications for education. SSRN Electronic Journal. https://doi.org/10.2139/ssrn.4312418 DOI: https://doi.org/10.2139/ssrn.4312418

Zhai, N., & Ma, X. (2022). Automated writing evaluation (AWE) feedback: A systematic investigation of college students’ acceptance. Computer Assisted Language Learning, 35(9), 2817-2842. DOI: https://doi.org/10.1080/09588221.2021.1897019

Zhang, X. (2024). An exploration of Chinese college students’ attitudes toward ChatGPT’s automated written corrective feedback on English essays. DOI: https://doi.org/10.70088/ymsdc047

Zhang, Z., & Hyland, K. (2018). Student engagement with teacher and automated feedback on L2 writing. Assessment & Evaluation in Higher Education, 43(7), 1082-1093. DOI: https://doi.org/10.1016/j.asw.2018.02.004

Zhang, R., Zou, D., & Cheng, G. (2023). Chatbot-based learning of logical fallacies in EFL writing: Perceived effectiveness in improving target knowledge and learner motivation. Interactive Learning Environments, 1–18. https://doi.org/10.1080/10494820.2023.2220374 DOI: https://doi.org/10.1080/10494820.2023.2220374

Zou, M., & Huang, L. (2023). The impact of ChatGPT on L2 writing and expected responses: Voice from doctoral students. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12397-x DOI: https://doi.org/10.1007/s10639-023-12397-x

Zhang (2024)

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2024-12-26

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Review

How to Cite

Zhang, Y. (2024). Incorporating ChatGPT as an automated written corrective feedback tool into L2 writing class. Journal of Language Teaching, 4(4), 22-34. https://doi.org/10.54475/jlt.2024.024

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