Examining the Role of AI-Powered Writing Assistants in Enhancing Critical Thinking In EFL Academic Writing
DOI:
https://doi.org/10.33394/jollt.v13i4.15077Keywords:
AI writing assistants, EFL academic writing, Critical thinking, AI feedback, Proficiency levelsAbstract
AI-driven writing assistants in EFL classrooms have revolutionized academic writing pedagogy, offering students immediate feedback on grammar, coherence, and organization. Although AI tools have demonstrated efficacy in improving linguistic precision, their influence on developing critical thinking remains ambiguous, especially among varying competency levels. Current study predominantly emphasizes AI's impact on grammatical corrections, although there is a paucity of knowledge on its effect on higher-order cognitive involvement, including argumentation and reasoning abilities. This study examines the interaction between EFL students and AI feedback, assessing its impact on promoting or obstructing critical thinking. The study reveals that, through examining pre-test and post-test writing evaluations, student reflections, and AI feedback patterns, lower-proficiency students (B1) predominantly depend on AI for superficial adjustments. In contrast, advanced learners (C1) interact with AI-generated ideas more critically. Nonetheless, AI's constraints in assessing argument strength and logical reasoning demonstrate that it cannot entirely supplant human feedback. These findings indicate that AI should be deliberately integrated with teacher support to optimize its advantages while reducing over-dependence. Future studies should investigate AI-human hybrid feedback models to improve language proficiency and critical thinking skills in academic writing.
References
Alam, A. (2021). Possibilities and Apprehensions in the Landscape of Artificial Intelligence in Education. 2021 International Conference on Computational Intelligence and Computing Applications (ICCICA), 1–8. https://doi.org/10.1109/ICCICA52458.2021.9697272
Alhassan, A. I. (2024). Analyzing the application of mixed method methodology in medical education: a qualitative study. BMC Medical Education, 24(1), 225. https://doi.org/10.1186/s12909-024-05242-3
Al-Sofi, B. B. M. A. (2024). Artificial intelligence-powered tools and academic writing: to use or not to use ChatGPT. Saudi Journal of Language Studies, 4(3), 145–161. https://doi.org/10.1108/SJLS-06-2024-0029
Apridayani, A., & Waluyo, B. (2025). Valuing students’ mindsets in essay compositions: Active learning and feedback approaches. Social Sciences & Humanities Open, 11, 101273. https://doi.org/10.1016/j.ssaho.2024.101273
Asrifan, A., Khristianto, K., Budiman, A., Astuti, P. I., & Rossydi, A. (2025). Enhancing Critical Thinking (pp. 413–448). https://doi.org/10.4018/979-8-3373-4576-5.ch012
Bai, B., & Wang, J. (2023). The role of growth mindset, self-efficacy and intrinsic value in self-regulated learning and English language learning achievements. Language Teaching Research, 27(1), 207–228. https://doi.org/10.1177/1362168820933190
Buragohain, D., Punpeng, G., Jaratjarungkiat, S., & Chaudhary, S. (2023). Impact of E-Learning Activities on English as a Second Language Proficiency among Engineering Cohorts of Malaysian Higher Education: A 7-Month Longitudinal Study. Informatics, 10(1), 31. https://doi.org/10.3390/informatics10010031
Cardon, P., Fleischmann, C., Aritz, J., Logemann, M., & Heidewald, J. (2023). The Challenges and Opportunities of AI-Assisted Writing: Developing AI Literacy for the AI Age. Business and Professional Communication Quarterly, 86(3), 257–295. https://doi.org/10.1177/23294906231176517
Fathi, J., Rahimi, M., & Teo, T. (2025). Applying intelligent personal assistants to develop fluency and comprehensibility, and reduce accentedness in EFL learners: an empirical study of Google Assistant. Language Teaching Research. https://doi.org/10.1177/13621688251317786
Fontenelle-Tereshchuk, D. (2025). First-Year College Students: Perspectives on Technology and Wellness in Education. Trends in Higher Education, 4(1), 13. https://doi.org/10.3390/higheredu4010013
Guo, X. (2024). Facilitator or thinking inhibitor: understanding the role of ChatGPT-generated written corrective feedback in language learning. Interactive Learning Environments, 1–19. https://doi.org/10.1080/10494820.2024.2445177
Kennedy, M. J., & Romig, J. E. (2024). Cognitive Load Theory: An Applied Reintroduction for Special and General Educators. TEACHING Exceptional Children, 56(6), 440–451. https://doi.org/10.1177/00400599211048214
Kim, J., Yu, S., Detrick, R., & Li, N. (2025). Exploring students’ perspectives on Generative AI-assisted academic writing. Education and Information Technologies, 30(1), 1265–1300. https://doi.org/10.1007/s10639-024-12878-7
Kormos, J., & Suzuki, S. (2024). Creativity and the linguistic features of argumentative and narrative written task performance. System, 127, 103531. https://doi.org/10.1016/j.system.2024.103531
Malik, M. A., Amjad, A. I., Aslam, S., & Fakhrou, A. (2024). Global insights: ChatGPT’s influence on academic and research writing, creativity, and plagiarism policies. Frontiers in Research Metrics and Analytics, 9. https://doi.org/10.3389/frma.2024.1486832
Mizumoto, A. (2023). Data-driven Learning Meets Generative AI: Introducing the Framework of Metacognitive Resource Use. Applied Corpus Linguistics, 3(3), 100074. https://doi.org/10.1016/j.acorp.2023.100074
Oates, A., & Johnson, D. (2025). ChatGPT in the Classroom: Evaluating its Role in Fostering Critical Evaluation Skills. International Journal of Artificial Intelligence in Education. https://doi.org/10.1007/s40593-024-00452-8
Pelenkahu, N., Ali, M. I., Tatipang, D. P., Wuntu, C. N., & Rorintulus, O. A. (2024). Metacognitive strategies and critical thinking in elevating EFL argumentative writing proficiency: Practical insights. Studies in English Language and Education, 11(2), 873–892. https://doi.org/10.24815/siele.v11i2.35832
Rajaram, K. (2023). Future of Learning: Teaching and Learning Strategies. In Learning Intelligence: Innovative and Digital Transformative Learning Strategies (pp. 3–53). Springer Nature Singapore. https://doi.org/10.1007/978-981-19-9201-8_1
Shanmugavelu, G., Parasuraman, B., Ariffin, K., Kannan, B., & Vadivelu, M. (2020). Inquiry Method in the Teaching and Learning Process. Shanlax International Journal of Education, 8(3), 6–9. https://doi.org/10.34293/education.v8i3.2396
Sharma, A., Bharti, & Pandey, A. (2024). Unleashing the Potential of Technology-Driven Learning Management Systems for Student-Centric Excellence to Empower Higher Education. RAiSE-2023, 195. https://doi.org/10.3390/engproc2023059195
Simms, R. C. (2024). Work With ChatGPT, Not Against. Nurse Educator, 49(3), 158–161. https://doi.org/10.1097/NNE.0000000000001634
Song, C., & Song, Y. (2023a). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1260843
Song, C., & Song, Y. (2023b). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in Psychology, 14. https://doi.org/10.3389/fpsyg.2023.1260843
Sridevi, R., Ashokkumar, P., & Sathish, V. (2024). Empowering Minds (pp. 125–152). https://doi.org/10.4018/979-8-3693-3559-8.ch005
Stuchlikova, L., & Weis, M. (2024). From Information to Insight: Reimagining Critical Thinking Pedagogy in the Age of Artificial Intelligence. 2024 International Conference on Emerging ELearning Technologies and Applications (ICETA), 591–598. https://doi.org/10.1109/ICETA63795.2024.10850787
Vieriu, A. M., & Petrea, G. (2025). The Impact of Artificial Intelligence (AI) on Students’ Academic Development. Education Sciences, 15(3), 343. https://doi.org/10.3390/educsci15030343
Vos, J., & van Rijn, B. (2025). Using mixed methods in feasibility studies: The example of brief transactional analysis psychotherapy for depression. Counselling and Psychotherapy Research, 25(1). https://doi.org/10.1002/capr.12871
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
Werdiningsih, I., Marzuki, & Rusdin, D. (2024). Balancing AI and authenticity: EFL students’ experiences with ChatGPT in academic writing. Cogent Arts & Humanities, 11(1). https://doi.org/10.1080/23311983.2024.2392388
Yadav, S. (2025). Leveraging AI to Enhance Teaching and Learning in Education. In Optimizing Research Techniques and Learning Strategies With Digital Technologies (pp. 211–238). IGI Global. https://doi.org/10.4018/979-8-3693-7863-2.ch008
Yin, X., Saad, M. R. B. M., & Halim, H. B. A. (2023). A systematic review of critical thinking instructional pedagogies in EFL writing: What do we know from a decade of research. Thinking Skills and Creativity, 49, 101363. https://doi.org/10.1016/j.tsc.2023.101363
Yusuf, A., Bello, S., Pervin, N., & Tukur, A. K. (2024). Implementing a proposed framework for enhancing critical thinking skills in synthesizing AI-generated texts. Thinking Skills and Creativity, 53, 101619. https://doi.org/10.1016/j.tsc.2024.101619
Zhai, C., & Wibowo, S. (2023). A systematic review on artificial intelligence dialogue systems for enhancing English as foreign language students’ interactional competence in the university. Computers and Education: Artificial Intelligence, 4, 100134. https://doi.org/10.1016/j.caeai.2023.100134
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: a systematic review. Smart Learning Environments, 11(1), 28. https://doi.org/10.1186/s40561-024-00316-7
Zhao, D. (2024). The impact of AI-enhanced natural language processing tools on writing proficiency: an analysis of language precision, content summarization, and creative writing facilitation. Education and Information Technologies. https://doi.org/10.1007/s10639-024-13145-5
Zhao, Y., Zhao, M., & Shi, F. (2023). Integrating Moral Education and Educational Information Technology: A Strategic Approach to Enhance Rural Teacher Training in Universities. Journal of the Knowledge Economy, 15(3), 15053–15093. https://doi.org/10.1007/s13132-023-01693-z
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