Exploring AI-Driven Adaptive Feedback in the Second Language Writing Skills Prompt AI Technology in Language Teaching
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Abstract
Recent developments in the field of artificial intelligence have changed CALL in the last decade, especially in terms of L2 writing. Therefore, the current research focuses on the extent to which AI-based adaptive feedback technologies in CALL improve L2 writing skills. It discusses the work AI does, the means it uses, and the theories it is based on when providing adaptive feedback, in light of the context, focusing on the role it plays in shaping particular educational pathways. The paper provides an overview of AI-integrated CALL tools that provide a measure of the tool’s effectiveness in generating useful feedback that helps in teaching L2 writing to meet real-world needs. Research findings and studies from different contexts support the use of these tools to improve learners’ L2 writing performance. Issues related to the use of AI-based adaptive feedback will also be addressed, including privacy, algorithm, and learner acceptance issues. By recommending the use of AI technology in language teaching, accompanied by human feedback, this study presents a constructive and moral model of how AI can be used without compromising its learning effect. Consequently, the results of the study show the potential benefits of using AI to generate adaptive feedback in improving L2 writing due to the immediacy, individualization, and possibility of iterating the feedback, which can help revolutionize language learning.
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References
Ai, H. (2017). Providing graduated corrective feedback in an intelligent computer-assisted language learning environment. ReCALL, 29(3), 313-334. https://doi.org/10.1017/S095834401700012X
Al Afnan, M. A., Dishari, S., Jovic, M., & Lomidze, K. (2023). ChatGPT as an Educational Tool: Opportunities, Challenges, and Rec-ommendations for Communication, Business Writing, and Composition Courses. Journal of Artificial Intelligence and Technology. https://doi.org/10.37965/jait.2023.0184.
Antoniadis, G., Granger, S., Kraif, O., Ponton, C., Medori, J., & Zampa, V. (2009). Integrated Digital Language Learning. Technolo-gy-Enhanced Learning: Principles and Products, 89–103. https://doi.org/10.1007/978-1-4020-9827-7_6
Beck, S., & Levine, S. (2023). Backtalk: ChatGPT: A powerful technology tool for writing instruction. Phi Delta Kappan, 105, 66 - 67. https://doi.org/10.1177/00317217231197487.
Bhowmik, S., & Chaudhuri, A. (2021). “I need my instructor to like to sit with me”: Addressing culture in L2 writing instruction. BC TEAL Journal, 6(1), 11-28. https://doi.org/10.14288/BCTJ.V6I1.387
Brown, D., Liu, Q., & Norouzian, R. (2023). Effectiveness of written corrective feedback in developing L2 accuracy: A Bayesian me-ta-analysis. Language Teaching Research, 13621688221147374. https://doi.org/10.1177/13621688221147374
Chen, X. (2022). L2 Students’ Adaptive Transfer Beyond First-Year Writing. INTESOL Journal, 19(1). https://doi.org/10.18060/26359
Curry, N., & Riordan, E. (2021). Intelligent CALL systems for writing development: investigating the use of write & improve for de-veloping written language and writing skills. In CALL Theory Applications for Online TESOL Education (pp. 252-273). IGI Global. https://doi.org/10.4018/978-1-7998-6609-1.CH011.
Dai, W., Lin, J., Jin, H., Li, T., Tsai, Y., Gašević, D., & Chen, G. (2023). Can Large Language Models Provide Feedback to Students? A Case Study on ChatGPT. In 2023 IEEE International Conference on Advanced Learning Technologies (ICALT) (pp. 323-325). https://doi.org/10.1109/ICALT58122.2023.00100.
Digel, S., Krause, T., & Biel, C. (2023). Enabling Individualized and Adaptive Learning–The Value of an AI-Based Recommender System for Users of Adult and Continuing Education Platforms. In International Conference on Artificial Intelligence in Education (pp. 797-803). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-36336-8_121
Dong, Y. (2023). Revolutionizing academic English writing through AI-powered pedagogy: practical exploration of teaching process and assessment. Journal of Higher Education Research, 4(2), 52. https://doi.org/10.32629/jher.v4i2.1188
Elola, I., & Oskoz, A. (2022). Reexamining feedback on L2 digital writing. Studies in Second Language Learning and Teaching, 12(4), 575-595. https://doi.org/10.14746/ssllt.2022.12.4.3
Escalante, J., Pack, A., & Barrett, A. (2023). AI-generated feedback on writing: insights into efficacy and ENL student preference. Inter-national Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00425-2
Ferris, D. R. (2012). Written corrective feedback in second language acquisition and writing studies. Language Teaching, 45(4), 446-459. https://doi.org/10.1017/S0261444812000250
Ferris, D. R. (2022). Feedback on L2 student writing: Current trends and future directions. In Handbook of practical second language teaching and learning (pp. 344-356). Routledge. https://doi.org/10.4324/9781003106609-28
Fleckenstein, J., Liebenow, L. W., & Meyer, J. (2023). Automated feedback and writing: A multi-level meta-analysis of effects on students’ performance. Frontiers in Artificial Intelligence, 6, 1162454. https://doi.org/10.3389/frai.2023.1162454
Hyland, K., & Hyland, F. (2019). Contexts and Issues in Feedback on L2 Writing. In K. Hyland & F. Hyland (Eds.), Feedback in Second Language Writing: Contexts and Issues (pp. 1–22). Chapter, Cambridge: Cambridge University Press. https://doi.org/10.1017/9781108635547.003
Jian, W., & Tengyao, Z. (2022). Probing into students’ use of automated feedback in essay revision: a case study of two Chinese EFL learners. The Journal of English Literacy Education: The Teaching and Learning of English as a Foreign Language, 9(2), 164-179. https://doi.org/10.36706/jele.v9i2.18349
Karimi, M. N., & Asadnia, F. (2022). Customizing Web 2.0 tools to writing pedagogy. Language Teacher Development in Digital Contexts, 57, 157. https://doi.org/10.1075/lllt.57.08kar
Katsarou, E., Wild, F., Sougari, A. M., & Chatzipanagiotou, P. (2023). A systematic review of voice-based intelligent virtual agents in EFL education. International Journal of Emerging Technologies in Learning (iJET), 18(10), 65-85. https://doi.org/10.3991/ijet.v18i10.37723
Kostikova, I. I., & Miasoiedova, S. V. (2019). Supporting post-graduate students writing skills development with the online machine learning tool: write & improve. Information Technologies and Learning Tools, 74(6), 238-249.https://doi.org/10.33407/itlt.v74i6.2600.
Mahmud, F. (2023). Investigating EFL Students' Writing Skills Through Artificial Intelligence: Wordtune Application as a Tool. Journal of Language Teaching and Research. https://doi.org/10.17507/jltr.1405.28.
Matsumura, L. C., Wang, E. L., Correnti, R., & Litman, D. (2022). Designing Automated Writing Evaluation Systems for Ambitious Instruction and Classroom Integration. In Artificial Intelligence in STEM Education (pp. 195-208). CRC Press. https://doi.org/10.1201/9781003181187-16
Mouchel, L., Wambsganss, T., Mejia-Domenzain, P., & Käser, T. (2023). Understanding Revision Behavior in Adaptive Writing Support Systems for Education. arXiv preprint arXiv:2306.10304.1. https://doi.org/10.5281/zenodo.8115766
Murad, I. A., Surameery, N. M. S., & Shakor, M. Y. (2023). Adopting ChatGPT to enhance educational experiences. International Journal of Information Technology & Computer Engineering, 3(05), 20-25. https://doi.org/10.55529/ijitc.35.20.25.
Parker, J., Becker, K., & Carroca, C. (2023). ChatGPT for Automated Writing Evaluation in Scholarly Writing Instruction. The Journal of nursing education, 62(12), 721-727. https://doi.org/10.3928/01484834-20231006-02.
Rad, H. S., Alipour, R., & Jafarpour, A. (2023). Using artificial intelligence to foster students’ writing feedback literacy, engagement, and outcome: A case of Wordtune application. Interactive Learning Environments, 1-21. https://doi.org/10.1080/10494820.2023.2208170
Shi, H., & Aryadoust, V. (2024). A systematic review of AI-based automated written feedback research. ReCALL, 36(2), 187–209. https://doi.org/10.1017/s0958344023000265
Shirazizadeh, M., & Amirfazlian, R. (2019). Improve Your Writing Online: www.writeandimprove.com. RELC Journal, 50, 491-492. https://doi.org/10.1177/0033688218756157.
Simonsen, H. K. (2021, July). AI writers in language learning. In 2021 International Conference on Advanced Learning Technologies (ICALT) (pp. 238-240). https://doi.org/10.1109/icalt52272.2021.00078
Troussas, C., Papakostas, C., Krouska, A., Mylonas, P., & Sgouropoulou, C. (2023, May). Personalized Feedback Enhanced by Natural Language Processing in Intelligent Tutoring Systems. In International Conference on Intelligent Tutoring Systems (pp. 667-677). Cham: Springer Nature Switzerland. https://doi.org/10.1007/978-3-031-32883-1_58
Wagner, J. P., & Wulf, D. J. (2016). Understanding Written Corrective Feedback in Second-Language Grammar Acquisition. Journal of Education and Learning, 5(4), 259-277. https://doi.org/10.5539/JEL.V5N4P259
Wahl, H., & Winiwarter, W. (2011, December). The intelligent integrated computer-assisted language learning (iiCALL) environment: work in progress. In Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services (pp. 426-429). https://doi.org/10.1145/2095536.2095622
Ward, M. (2019). Joining the blocks together – an NLP pipeline for CALL development. CALL and Complexity – Short Papers from EU-ROCALL 2019 (pp. 397–401). https://doi.org/10.14705/rpnet.2019.38.1043
Wei, P., Wang, X., & Dong, H. (2023). The impact of automated writing evaluation on second language writing skills of Chinese EFL learners: a randomized controlled trial. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1249991
Woo, J. H., & Choi, H. (2021). Systematic Review for AI-based Language Learning Tools. Journal of Digital Contents Society, 22(11), 1783–1792. https://doi.org/10.9728/dcs.2021.22.11.1783
Woodworth, J. (2023). The Use of Hybrid Corrective Feedback in the Foreign Language Classroom and Its Implications for Teacher Education: A Case Study with Chinese Learners in an EAP Setting. In The Future of Teacher Education (pp. 200-227). Brill. https://doi.org/10.1163/9789004678545_009
Woodworth, J., & Barkaoui, K. (2020). Perspectives on using automated writing evaluation systems to provide written corrective feedback in the ESL classroom. TESL Canada Journal, 37(2), 234–247. https://doi.org/10.18806/tesl.v37i2.1340
Yang, H., Gao, C., & Shen, H. Z. (2024). Learner interaction with, and response to, AI-programmed automated writing evaluation feed-back in EFL writing: An exploratory study. Education and Information Technologies, 29(4), 3837-3858.
Zhang, X., & Zhang, R. (2023). Feedback, Response, and Learner Development: A Sociocultural Approach to Corrective Feedback in Second Language Writing. SAGE Open, 13(1), 21582440231157680. https://doi.org/10.1177/21582440231157680
Zhao, X. (2022). Leveraging Artificial Intelligence (AI) Technology for English Writing: Introducing Wordtune as a Digital Writing Assistant for EFL Writers. RELC Journal, 54, 890-894. https://doi.org/10.1177/00336882221094089