ỨNG DỤNG CHATGPT TRONG HỌC TẬP TỰ ĐIỀU CHỈNH Ở HỌC PHẦN PHIÊN DỊCH: NHẬN THỨC VÀ THỰC HÀNH CỦA SINH VIÊN
Nội dung chính của bài viết
Tóm tắt
Trí tuệ nhân tạo (AI) ngày càng được ứng dụng để hỗ trợ quá trình học tập tự điều chỉnh (SRL) của sinh viên trong môi trường học tập số. Nghiên cứu này xem xét quan điểm và thực hành của sinh viên Việt Nam trong việc sử dụng ChatGPT nhằm phục vụ học tập tự điều chỉnh trong học phần phiên dịch. Dựa trên mô hình học tập tự điều chỉnh theo chu trình của Zimmerman, nghiên cứu phân tích cách sinh viên tương tác với ChatGPT ở ba giai đoạn: chuẩn bị (forethought), thực hiện (performance) và tự phản tư (self-reflection). Nghiên cứu sử dụng phương pháp hỗn hợp, bao gồm: khảo sát bằng bảng hỏi (n = 178), phỏng vấn nhóm (n = 24) và phản hồi có định hướng (n = 80), để thu được cái nhìn rõ ràng và toàn diện về trải nghiệm của sinh viên. Kết quả cho thấy sinh viên đánh giá ChatGPT là một công cụ hữu ích cho việc luyện tập các bài thực hành phiên dịch trực tuyến, đặc biệt ở các giai đoạn chuẩn bị và tự phản tư. Sinh viên cho rằng ChatGPT có thể hỗ trợ cả về mặt ngôn ngữ và cảm xúc, đưa ra phản hồi tức thời giúp họ tự đánh giá và cải thiện năng lực phiên dịch. Tuy nhiên, mức độ hiệu quả của ChatGPT có sự khác biệt tùy thuộc vào trình độ ngôn ngữ của sinh viên cũng như khả năng quản lý và sử dụng công cụ này. Bên cạnh đó, ChatGPT cũng gặp phải những thách thức khi đánh giá các yếu tố văn hóa trong các nhiệm vụ phiên dịch. Kết quả nghiên cứu nhấn mạnh tầm quan trọng của năng lực số và khả năng siêu nhận thức của sinh viên khi sử dụng ChatGPT, đồng thời cho thấy cần có sự định hướng sư phạm nhằm tích hợp hiệu quả công cụ AI này vào quá trình học tập tự điều chỉnh.
Từ khóa
học tập tự điều chỉnh, phiên dịch, nhận thức, thực hành
Chi tiết bài viết
Tài liệu tham khảo
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Baker, R. S. (2016). Stupid tutoring systems, intelligent humans. International Journal of Artificial Intelligence in Education, 26(2), 600-614. https://doi.org/10.1007/s40593-016-0105-0
Barak, M. (2010). Motivating self-regulated learning in technology education. International Journal of Technology and Design Education, 20(4), 381-401. https://doi.org/10.1007/s10798-009-9092-x
Burruss, G. W., & Johnson, A. (2021). Online survey research. In J. C. Barnes, David R. Forde (Eds.), The Encyclopedia of Research Methods in Criminology and Criminal Justice (Chapter 21). https://doi.org/10.1002/9781119111931.ch21
Chan, V. (2023). Investigating the impact of a virtual reality mobile application on learners' interpreting competence. Journal of Computer Assisted Learning, 39(4), 1242-1258. https://doi.org/10.1111/jcal.12796
Chiu, T. K., Meng, H., Chai, C. S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum. IEEE Transactions on Education, 65(1), 30-39. https://doi.org/10.1109/TE.2021.3085878
Cox, E., & Salaets, H. (2019). Accuracy: Omissions in consecutive versus simultaneous interpreting. International Journal of Interpreter Education, 11(2), Article 7. https://tigerprints.clemson.edu/ijie/vol11/iss2/7
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Dinh, C. T. (2025). EFL Students’ Perspectives on ChatGPT in Translation: Exploring AI Assistance, Motivation, and Learning Outcomes. Electronic Journal of e-Learning, 23(2), 99-116. https://doi.org/10.34190/ejel.23.2.4006
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Fitria, T. N. (2023). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum: Journal of English Language Teaching 12(1), 44-58. https://www.researchgate.net/publication/369821682_Artificial_intelligence_AI_technology_in_OpenAI_ChatGPT_application_A_review_of_ChatGPT_in_writing_English_essay
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Gile, D. (2009). Basic concepts and models for interpreter and translator training (Rev. ed.). John Benjamins. https://doi.org/10.1075/btl.8
He, X., & Kang, S., M. (2025). The Application of ChatGPT in Chinese MTI Students' Autonomous Learning. Arab World English Journal (AWEJ) Special Issue on Artificial Intelligence, 176-192. https://doi.org/10.24093/awej/AI.10
Hsu, T. C., Chang, C., & Jen, T. H. (2024). Artificial intelligence image recognition using self-regulation learning strategies: effects on vocabulary acquisition, learning anxiety, and learning behaviours of English language learners. Interactive Learning Environments, 32(6), 3060-3078. https://doi.org/10.1080/10494820.2023.2165508
Hu, G. (2006). Adaptation in consecutive interpreting. Perspectives: Studies in Translation Theory and Practice, 14(1), 3-12. https://doi.org/10.1080/09076760608669013
Hu, P., Gao, B., & Li, K. (2025). Learning interpreting in virtual reality: a scoping review. Interactive Learning Environments, 33(1), 347-366. https://doi.org/10.1080/10494820.2024.2347304
Jia, Y., & Aryadoust, V. (2024). The Utility of Generative Artificial Intelligence in Rating Interpreters’ Accuracy: A Case Study of ChatGPT-4. In C. A. Chapelle, G. H. Beckett, & J. Ranalli (Eds.), Exploring artificial intelligence in applied linguistics (pp. 59-72). https://doi.org/10.31274/isudp.2024.154.05
Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069-6104. https://doi.org/10.1007/s10639-021-10831-6
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
Kusmaryono, I., & Wijayanti, D. (2022). Number of response options, reliability, validity, and potential bias in the use of the Likert scale education and social science research: A literature review. International Journal of Educational Methodology, 8(4), 625-637. https://doi.org/10.12973/ijem.8.4.625
Liu, Y., Luo, W., & Wang, X. (2023). Exploring the relationship between students’ note-taking and interpreting quality: a case study in the Chinese context. Frontiers in Education, 8, 1157509. https://doi.org/10.3389/feduc.2023.1157509
Lu, L. & Chen, Y. (2013). A survey of short-term memory in consecutive interpreting courses. In X. Shao (Ed.), Proceedings of the 2013 International Academic Workshop on Social Science (pp. 671-674). Atlantis Press. https://doi.org/10.2991/iaw-sc.2013.148
Ma, J. (2013). A Study of Interpreting Skills from the Perspective of Interpreting Process. Journal of Language Teaching and Research, 4(6), 1232-1237. https://doi.org/10.4304/jltr.4.6.1232-1237
Moratto, R., & Yang, Z. (2024). Probing the cognitive load of consecutive interpreters: A corpus-based study. Translation and Interpreting Studies, 19(2), 234–256, https://doi.org/10.1075/tis.22047.mor
Muthuprasad, T., Aiswarya, S., Aditya, K., & Jha, G. K. (2020). Students’ perception and preference for online education in India during COVID-19 pandemic. Social Sciences & Humanities Open, 3(1), 100101. https://doi.org/10.1016/j.ssaho.2020.100101
Ng, D. T. K., Tan, C. W., & Leung, J. K. L. (2024). Empowering student self‐regulated learning and science education through ChatGPT: A pioneering pilot study. British Journal of Educational Technology, 55(4), 1328-1353. https://doi.org/10.1111/bjet.13454
Ortlipp, M. (2008). Keeping and using reflective journals in the qualitative research process. The qualitative report, 13(4), 695-705. https://doi.org/10.46743/2160-3715/2008.1579
Oxford, R. L. (2011). Strategies for learning a second or foreign language. Language Teaching, 44(2), 167-180. https://doi.org/10.1017/S0261444810000492
Pöchhacker, F. (2022). Introducing Interpreting Studies (3rd ed.). Routledge. https://doi.org/10.4324/9781003186472
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in psychology, 14, 1255594. https://doi.org/10.3389/fpsyg.2023.1255594
Rodway, P., & Schepman, A. (2023). The impact of adopting AI educational technologies on projected course satisfaction in university students. Computers and Education: Artificial Intelligence, 5, 100150. https://doi.org/10.1016/j.caeai.2023.100150
Sahari, Y., Al-Kadi, A. M. T., & Ali, J. K. M. (2023). A cross sectional study of ChatGPT in translation: Magnitude of use, attitudes, and uncertainties. Journal of Psycholinguistic Research, 52(6), 2937-2954. https://doi.org/10.1007/s10936-023-10031-y
Sandrelli, A. (2015). Becoming an interpreter: The role of computer technology. MonTI (Special Issue 2), 111–138. https://doi.org/10.6035/MonTI.2015.ne2.4
Saputra, I., Mahniza, M., Novelni, R., Putri, E. Y., Thaitami, S. H., & Nurhayati, A. (2025). Cognitive and Contextual Dimensions of Self-regulated Learning in AI-driven Digital Classrooms. Edu Research, 6(2), 1168-1179. https://iicls.org/index.php/jer/article/view/924
Son, J. B., & Jin, T. (2024). How to Exploit China’s AI-powered Platforms for Korean-Chinese Translation/Interpreting Education. INContext: Studies in Translation and Interculturalism, 4(1), 31-52. http://doi.org/10.54754/incontext.v4i1.75
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
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Zhang, R., & Zou, D. (2022). Types, purposes, and effectiveness of state-of-the-art technologies for second and foreign language learning. Computer Assisted Language Learning, 35(4), 696-742. https://doi.org/10.1080/09588221.2020.1744666
Zhang, X. (2011). On Interpreters’ Intercultural Awareness. World Journal of English Language, 1(1), 47. https://doi.org/10.5430/wjel.v1n1p47
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American educational research journal, 45(1), 166-183. http://aer.sagepub.com/content/45/1/166
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7
Zimmerman, B. J., & Schunk, D. H. (2011). Handbook of self-regulation of learning and performance. Routledge. https://www.google.com.vn/books/edition/Handbook_of_Self_Regulation_of_Learning/XfOYV0lwzGgC?hl=en&gbpv=0
Zimmerman, B. J., & Schunk, D. H. (2012). Motivation: An essential dimension of self-regulated learning. In Motivation and self-regulated learning (pp. 1-30). Routledge. https://doi.org/10.4324/9780203831076
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Baker, R. S. (2016). Stupid tutoring systems, intelligent humans. International Journal of Artificial Intelligence in Education, 26(2), 600-614. https://doi.org/10.1007/s40593-016-0105-0
Barak, M. (2010). Motivating self-regulated learning in technology education. International Journal of Technology and Design Education, 20(4), 381-401. https://doi.org/10.1007/s10798-009-9092-x
Burruss, G. W., & Johnson, A. (2021). Online survey research. In J. C. Barnes, David R. Forde (Eds.), The Encyclopedia of Research Methods in Criminology and Criminal Justice (Chapter 21). https://doi.org/10.1002/9781119111931.ch21
Chan, V. (2023). Investigating the impact of a virtual reality mobile application on learners' interpreting competence. Journal of Computer Assisted Learning, 39(4), 1242-1258. https://doi.org/10.1111/jcal.12796
Chiu, T. K., Meng, H., Chai, C. S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum. IEEE Transactions on Education, 65(1), 30-39. https://doi.org/10.1109/TE.2021.3085878
Cox, E., & Salaets, H. (2019). Accuracy: Omissions in consecutive versus simultaneous interpreting. International Journal of Interpreter Education, 11(2), Article 7. https://tigerprints.clemson.edu/ijie/vol11/iss2/7
deMarrais, K. B. (Ed.). (2012). Inside stories: Qualitative research reflections. Routledge. https://books.google.com.vn/books/about/Inside_Stories.html?hl=fr&id=Wak75DXdwV4C&redir_esc=y
Dinh, C. T. (2025). EFL Students’ Perspectives on ChatGPT in Translation: Exploring AI Assistance, Motivation, and Learning Outcomes. Electronic Journal of e-Learning, 23(2), 99-116. https://doi.org/10.34190/ejel.23.2.4006
Dizon, G., Gold, J., & Barnes, R. (2025). ChatGPT for self-regulated language learning: University English as a foreign language students’ practices and perceptions. Digital Applied Linguistics, 3, 102510. https://doi.org/10.29140/dal.v3.102510
Fitria, T. N. (2023). Artificial intelligence (AI) technology in OpenAI ChatGPT application: A review of ChatGPT in writing English essay. ELT Forum: Journal of English Language Teaching 12(1), 44-58. https://www.researchgate.net/publication/369821682_Artificial_intelligence_AI_technology_in_OpenAI_ChatGPT_application_A_review_of_ChatGPT_in_writing_English_essay
Gile, D. (2001). Consecutive vs. Simultaneous: Which is more accurate? Interpretation Studies: The Journal of the Japan Association for Interpretation Studies, 1, 8-20. https://doi.org/10.50837/istk.0103
Gile, D. (2009). Basic concepts and models for interpreter and translator training (Rev. ed.). John Benjamins. https://doi.org/10.1075/btl.8
He, X., & Kang, S., M. (2025). The Application of ChatGPT in Chinese MTI Students' Autonomous Learning. Arab World English Journal (AWEJ) Special Issue on Artificial Intelligence, 176-192. https://doi.org/10.24093/awej/AI.10
Hsu, T. C., Chang, C., & Jen, T. H. (2024). Artificial intelligence image recognition using self-regulation learning strategies: effects on vocabulary acquisition, learning anxiety, and learning behaviours of English language learners. Interactive Learning Environments, 32(6), 3060-3078. https://doi.org/10.1080/10494820.2023.2165508
Hu, G. (2006). Adaptation in consecutive interpreting. Perspectives: Studies in Translation Theory and Practice, 14(1), 3-12. https://doi.org/10.1080/09076760608669013
Hu, P., Gao, B., & Li, K. (2025). Learning interpreting in virtual reality: a scoping review. Interactive Learning Environments, 33(1), 347-366. https://doi.org/10.1080/10494820.2024.2347304
Jia, Y., & Aryadoust, V. (2024). The Utility of Generative Artificial Intelligence in Rating Interpreters’ Accuracy: A Case Study of ChatGPT-4. In C. A. Chapelle, G. H. Beckett, & J. Ranalli (Eds.), Exploring artificial intelligence in applied linguistics (pp. 59-72). https://doi.org/10.31274/isudp.2024.154.05
Kim, J., Lee, H., & Cho, Y. H. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in education. Education and Information Technologies, 27(5), 6069-6104. https://doi.org/10.1007/s10639-021-10831-6
Kohnke, L., Moorhouse, B. L., & Zou, D. (2023). ChatGPT for language teaching and learning. RELC Journal, 54(2), 537-550. https://doi.org/10.1177/00336882231162868
Kusmaryono, I., & Wijayanti, D. (2022). Number of response options, reliability, validity, and potential bias in the use of the Likert scale education and social science research: A literature review. International Journal of Educational Methodology, 8(4), 625-637. https://doi.org/10.12973/ijem.8.4.625
Liu, Y., Luo, W., & Wang, X. (2023). Exploring the relationship between students’ note-taking and interpreting quality: a case study in the Chinese context. Frontiers in Education, 8, 1157509. https://doi.org/10.3389/feduc.2023.1157509
Lu, L. & Chen, Y. (2013). A survey of short-term memory in consecutive interpreting courses. In X. Shao (Ed.), Proceedings of the 2013 International Academic Workshop on Social Science (pp. 671-674). Atlantis Press. https://doi.org/10.2991/iaw-sc.2013.148
Ma, J. (2013). A Study of Interpreting Skills from the Perspective of Interpreting Process. Journal of Language Teaching and Research, 4(6), 1232-1237. https://doi.org/10.4304/jltr.4.6.1232-1237
Moratto, R., & Yang, Z. (2024). Probing the cognitive load of consecutive interpreters: A corpus-based study. Translation and Interpreting Studies, 19(2), 234–256, https://doi.org/10.1075/tis.22047.mor
Muthuprasad, T., Aiswarya, S., Aditya, K., & Jha, G. K. (2020). Students’ perception and preference for online education in India during COVID-19 pandemic. Social Sciences & Humanities Open, 3(1), 100101. https://doi.org/10.1016/j.ssaho.2020.100101
Ng, D. T. K., Tan, C. W., & Leung, J. K. L. (2024). Empowering student self‐regulated learning and science education through ChatGPT: A pioneering pilot study. British Journal of Educational Technology, 55(4), 1328-1353. https://doi.org/10.1111/bjet.13454
Ortlipp, M. (2008). Keeping and using reflective journals in the qualitative research process. The qualitative report, 13(4), 695-705. https://doi.org/10.46743/2160-3715/2008.1579
Oxford, R. L. (2011). Strategies for learning a second or foreign language. Language Teaching, 44(2), 167-180. https://doi.org/10.1017/S0261444810000492
Pöchhacker, F. (2022). Introducing Interpreting Studies (3rd ed.). Routledge. https://doi.org/10.4324/9781003186472
Qiao, H., & Zhao, A. (2023). Artificial intelligence-based language learning: illuminating the impact on speaking skills and self-regulation in Chinese EFL context. Frontiers in psychology, 14, 1255594. https://doi.org/10.3389/fpsyg.2023.1255594
Rodway, P., & Schepman, A. (2023). The impact of adopting AI educational technologies on projected course satisfaction in university students. Computers and Education: Artificial Intelligence, 5, 100150. https://doi.org/10.1016/j.caeai.2023.100150
Sahari, Y., Al-Kadi, A. M. T., & Ali, J. K. M. (2023). A cross sectional study of ChatGPT in translation: Magnitude of use, attitudes, and uncertainties. Journal of Psycholinguistic Research, 52(6), 2937-2954. https://doi.org/10.1007/s10936-023-10031-y
Sandrelli, A. (2015). Becoming an interpreter: The role of computer technology. MonTI (Special Issue 2), 111–138. https://doi.org/10.6035/MonTI.2015.ne2.4
Saputra, I., Mahniza, M., Novelni, R., Putri, E. Y., Thaitami, S. H., & Nurhayati, A. (2025). Cognitive and Contextual Dimensions of Self-regulated Learning in AI-driven Digital Classrooms. Edu Research, 6(2), 1168-1179. https://iicls.org/index.php/jer/article/view/924
Son, J. B., & Jin, T. (2024). How to Exploit China’s AI-powered Platforms for Korean-Chinese Translation/Interpreting Education. INContext: Studies in Translation and Interculturalism, 4(1), 31-52. http://doi.org/10.54754/incontext.v4i1.75
Song, C., & Song, Y. (2023). Enhancing academic writing skills and motivation: assessing the efficacy of ChatGPT in AI-assisted language learning for EFL students. Frontiers in psychology, 14, 1260843. https://doi.org/10.3389/fpsyg.2023.1260843
Subedi, K. R. (2021). Determining the sample in qualitative research. Scholars’ Journal, 4(1), 1-13. https://doi.org/10.3126/scholars.v4i1.42457
Tlili, A., Shehata, B., Adarkwah, M. A., Bozkurt, A., Hickey, D. T., Huang, R., & Agyemang, B. (2023). What if the devil is my guardian angel: ChatGPT as a case study of using chatbots in education. Smart learning environments, 10(1), 15. https://doi.org/10.1186/s40561-023-00237-x
Wang, B. (2015). Bridging the gap between interpreting classrooms and real-world interpreting. International journal of interpreter education, 7(1), 6. https://tigerprints.clemson.edu/ijie/vol7/iss1/6
Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955
Ye, H. (2020). Digital technology-based pedagogy for interpreting. In International Conference on Application of Intelligent Systems in Multi-modal Information Analytics (pp. 521-527). Springer, Cham: Springer International Publishing. https://doi.org/10.1007/978-3-030-51431-0_76
Yin, R. K. (2009). Case study research: Design and methods (4th ed.). Sage Publications. https://www.google.com.vn/books/edition/Case_Study_Research/FzawIAdilHkC?hl=en&gbpv=0
Zhang, R., & Zou, D. (2022). Types, purposes, and effectiveness of state-of-the-art technologies for second and foreign language learning. Computer Assisted Language Learning, 35(4), 696-742. https://doi.org/10.1080/09588221.2020.1744666
Zhang, X. (2011). On Interpreters’ Intercultural Awareness. World Journal of English Language, 1(1), 47. https://doi.org/10.5430/wjel.v1n1p47
Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American educational research journal, 45(1), 166-183. http://aer.sagepub.com/content/45/1/166
Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7
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