Research Article

Leveraging AI to enhance writing skills of senior TFL students in Kazakhstan: A case study using “Write & Improve”

Abbas Bodaubekov 1 , Shakhrizat Agaidarova 1 , Talgat Zhussipbek 2 3 , Davronzhon Gaipov 1 , Nuri Balta 1 *
More Detail
1 SDU University, Almaty, KAZAKHSTAN2 Karaganda Buketov University, Karaganda, KAZAKHSTAN3 Michigan State University, East Lansing, MI, USA* Corresponding Author
Contemporary Educational Technology, 17(1), January 2025, ep548, https://doi.org/10.30935/cedtech/15687
Published Online: 05 December 2024, Published: 01 January 2025
OPEN ACCESS   734 Views   197 Downloads
Download Full Text (PDF)

ABSTRACT

This study investigates the effectiveness of feedback provided by teachers versus feedback generated by the Write & Improve platform in enhancing the writing skills of senior undergraduate students enrolled in a “two foreign language” program at a private university in Kazakhstan. The quasi-experimental design involved four teachers, each teaching one control and one experimental class, totaling eight groups of students. Pre- and post-tests were conducted over a period of five weeks, focusing on task achievement, coherence and cohesion, lexical resource, grammar and accuracy, and overall score. Data analysis included descriptive statistics, Mann-Whitney U tests for pre-test comparisons, and MANCOVA analyses for post-test comparisons. Results show no significant difference in the impact of Write & Improve feedback compared to traditional teacher feedback across multiple dimensions of the writing test, both within individual teachers’ classes and when combined. Longitudinal analysis reveals fluctuating scores over time with no consistent improvement. Thus, the study concludes that the Write & Improve tool is equally effective as teacher feedback in improving students’ writing skills. This implies that educational institutions can potentially integrate technology-based feedback systems like Write & Improve alongside traditional teaching methods to enhance student learning outcomes in writing proficiency.

CITATION (APA)

Bodaubekov, A., Agaidarova, S., Zhussipbek, T., Gaipov, D., & Balta, N. (2025). Leveraging AI to enhance writing skills of senior TFL students in Kazakhstan: A case study using “Write & Improve”. Contemporary Educational Technology, 17(1), ep548. https://doi.org/10.30935/cedtech/15687

REFERENCES

  1. Alammari, A., & Abdel-Reheem Amin, E. (2023). EFL students’ perception of using AI paraphrasing tools in English language research projects. Arab World English Journals, 14(3). https://doi.org/10.24093/awej/vol14no3.11
  2. Almaiah, M. A., Alfaisal, R., Salloum, S. A., Hajjej, F., Thabit, S., El-Qirem, F. A., Lutfi, A., Alrawad, M., Al Mulhem, A., Alkhdour, T., Awad, A. B., & Al-Maroof, R. S. (2022). Examining the impact of artificial intelligence and social and computer anxiety in e-learning settings: Students’ perceptions at the university level. Electronics, 11(22), Article 3662. https://doi.org/10.3390/electronics11223662
  3. Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20, Article 43. https://doi.org/10.1186/s41239-023-00411-8
  4. Cheng, G. (2017). The impact of online automated feedback on students’ reflective journal writing in an EFL course. The Internet and Higher Education, 34, 18–27. https://doi.org/10.1016/j.iheduc.2017.04.002
  5. Chounta, I. A., Bardone, E., Raudsep, A., & Pedaste, M. (2022). Exploring teachers’ perceptions of Artificial Intelligence as a tool to support their practice in Estonian K-12 education. International Journal of Artificial Intelligence in Education, 32(3), 725–755. https://doi.org/10.1007/s40593-021-00243-5
  6. Curry, N., & Riordan, E. (2021). Intelligent CALL systems for writing development: Investigating the use of Write & Improve for developing written language and writing skills. In K. Kelch, P. Byun, S. Safavi, & S. Cervantes (Eds.), CALL theory applications for online TESOL education (pp. 252–273). IGI Global. https://doi.org/10.4018/978-1-7998-6609-1.ch011
  7. de los Ángeles Domínguez-González, M., Hervás-Gómez, C., Díaz-Noguera, M. D., & Reina-Parrado, M. (2023). Attention to diversity from artificial intelligence. The European Educational Researcher, 6(3), 101–115. https://doi.org/10.31757/euer.633
  8. Fitria, T. N. (2021). Artificial intelligence (AI) in education: Using AI tools for teaching and learning process. In Proceedings of the National Seminar (pp. 134–147).
  9. Gravetter, F. J., Forzano, L. A. B., & Rakow, T. (2009). Research methods for the behavioral sciences. Cengage Learning.
  10. Hadžimehmedagić, M., & Akbarov, A. (2014). Traditional vs modern teaching methods. Advantages and disadvantages. CORE. https://core.ac.uk/download/pdf/153448544.pdf
  11. Hattie, J., & Timperley, H. (2007). The power of feedback. Review of Educational Research, 77(1), 81–112. https://doi.org/10.3102/003465430298487
  12. Hervás Gómez, C., & Toledo Morales, P. (2018). Real and ideal perception of the intelligent classroom environment of future teachers. Journal of Research in Science, Mathematics and Technology Education, 1(1), 91–111. https://doi.org/10.31756/jrsmte.115
  13. Heydari, M. & Marefat, F. (2020). Integrating computer- and teacher-provided feedback in an EFL academic writing context. In L. McCallum, & Coombe (Eds.), The assessment of L2 written English across the MENA Region (pp. 297–323). Palgrave Macmillan. https://doi.org/10.1007/978-3-030-53254-3_13
  14. Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education promises and implications for teaching and learning. Center for Curriculum Redesign.
  15. Hussain, I. (2020). Attitude of university students and teachers towards instructional role of artificial intelligence. International Journal of E-Learning and Distance Education, 5, 158–177. https://doi.org/10.36261/ijdeel.v5i2.1057
  16. Karpova, K. (2021). Integration of “Write and Improve” AWE tool into EFL at higher educational establishment: case study. Celtic: A Journal of Culture English Language Teaching Literature & Linguistic, 7, 137–150. https://doi.org/10.22219/celtic.v7i2.14036
  17. Kompa, J. S. (2012). Disadvantages of teacher-centered learning. Joana Stella Kompa. https://joanakompa.com/2012/06/25/the-key-disadvantages-of-teacher-centered-learning/
  18. Kukulska-Hulme, A., & Shield, L. (2008). An overview of mobile assisted language learning: From content delivery to supported collaboration and interaction. ReCALL, 20(3), 271–289. https://doi.org/10.1017/S0958344008000335
  19. Luckin, R. (2017). Towards artificial intelligence-based assessment systems. Nature Human Behaviour, 1(3), Article 0028. https://doi.org/10.1038/s41562-016-0028
  20. Luckin, R., & Holmes, W. (2016). Intelligence unleashed: An argument for AI in education. Pearson.
  21. McGrath, C., Pargman, T. C., Juth, N., & Palmgren, P. J. (2023). University teachers’ perceptions of responsibility and artificial intelligence in higher education-An experimental philosophical study. Computers and Education: Artificial Intelligence, 4, Article 100139. https://doi.org/10.1016/j.caeai.2023.100139
  22. Nazaretsky, T., Cukurova, M., & Alexandron, G. (2022). An instrument for measuring teachers’ trust in AI-based educational technology. In Proceedings of the 12th International Learning Analytics and Knowledge Conference (pp. 56–66). https://doi.org/10.1145/3506860.3506866
  23. Niemi, H., & Niu, S. J. (2021). Digital storytelling enhancing Chinese primary school students’ self-efficacy in mathematics learning. Journal of Pacific Rim Psychology, 15. https://doi.org/10.1177/1834490921991432
  24. Pavela, G. (1997). Applying the power of association on campus: A model code of academic integrity. Journal of College and University Law, 24, 97–118.
  25. Relmasira, S. C., Lai, Y. C., & So, C. F. H. (2021). Future jobs: Indonesian primary students’ aspirations and teachers’ predictions. The European Educational Researcher, 4(2), 209–225. https://doi.org/10.31757/euer.425
  26. Ribble, M. (2015). Digital citizenship in schools: Nine elements all students should know. International Society for Technology in Education.
  27. Robin B. R. (2008). Digital storytelling: A powerful technology tool for the 21st century classroom. Theory Into Practice, 47(3), 220–228. https://doi.org/10.1080/00405840802153916
  28. Schwerdt, G., & Wuppermann, A. C. (2011). Is traditional teaching really all that bad? A within-student between-subject approach. Economics of Education Review, 30(2), 365–379. https://doi.org/10.1016/j.econedurev.2010.11.005
  29. Shadish, W. R., Cook, T. D., & Campbell, D. T. (2002). Experimental and quasi-experimental designs for generalized causal inference. Houghton Mifflin Company.
  30. Sit, C., Srinivasan, R., Amlani, A., Muthuswamy, K., Azam, A., Monzon, L., & Poon, D. S. (2020). Attitudes and perceptions of UK medical students towards artificial intelligence and radiology: A multicentre survey. Insights into Imaging, 11, Article 14. https://doi.org/10.1186/s13244-019-0830-7
  31. Sumakul, D. T. Y., Hamied, F. A., & Sukyadi, D. (2022). Artificial intelligence in EFL classrooms: Friend or foe? LEARN Journal: Language Education and Acquisition Research Network, 15(1), 232–256.
  32. Taskiran, A., & Goksel, N. (2022). Automated feedback and teacher feedback: Writing achievement in learning English as a foreign language at a distance. The Turkish Online Journal of Distance Education, 23(2), 120–139. https://doi.org/10.17718/tojde.1096260
  33. Timonen, P., & Ruokamo, H. (2021). Designing a preliminary model of coaching pedagogy for synchronous collaborative online learning. Journal of Pacific Rim Psychology, 15. https://doi.org/10.1177/1834490921991430
  34. Toscano, M. A. (2023). Write & Improve tool and writing skill [Bachelor’s thesis, Universidad Técnica de Ambato].
  35. Väätäinen, J., & Ruokamo, H. (2021). Conceptualizing dimensions and a model for digital pedagogy. Journal of Pacific Rim Psychology, 15. https://doi.org/10.1177/1834490921995395
  36. Wali, F., & Huijser, H. (2018). Write to improve: Exploring the impact of an automated feedback tool on Bahraini learners of English. Learning & Teaching in Higher Education: Gulf Perspectives, 15(1), 14–34. https://doi.org/10.18538/lthe.v15.n1.293
  37. Wang, Y., Shang, H., & Briody, P. (2013). Exploring the impact of using automated writing evaluation in English as a foreign language university students’ writing. Computer Assisted Language Learning, 26(3), 234–257. https://doi.org/10.1080/09588221.2012.655300
  38. Yau, K. W., Chai, C. S., Chiu, T. K., Meng, H., King, I., & Yam, Y. (2023). A phenomenographic approach on teacher conceptions of teaching artificial intelligence (AI) in K-12 schools. Education and Information Technologies, 28, 1041–1064. https://doi.org/10.1007/s10639-022-11161-x
  39. Yilmaz, H., Maxutov, S., Baitekov, A. & Balta, N. (2023). Student’s perception of ChatGPT: A technology acceptance model study. International Educational Review, 1(1), 57– 83. https://doi.org/10.58693/ier.114
  40. Zaghlool, Z. D., & Khasawneh, M. A. S. (2023). Incorporating the impacts and limitations of AI-driven feedback, evaluation, and real-time conversation tools in foreign language learning. Migration Letters, 20(7), 1071–1083.