Assessment of Translation Competence Development Needs of Foreign Language Majors at Guangxi University of Foreign Languages
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Published
Oct 30, 2025
Abstract
This study investigated the translation competence (TC) development needs of foreign language majors at Guangxi University of Foreign Languages (GUFL) amid the AI-driven transformation of the translation industry. Employing a quantitative approach, the study administered a questionnaire to a sample of 359 students, with data analyzed via SPSS for descriptive statistics, correlation, and gap analysis. The research identified ten TC dimensions: Strategic Competence (SC), Critical Thinking (CT), Language Competence (LC), Intercultural Competence (IC), Translation Knowledge (TK), Thematic Competence (ThC), Technology Competence (TechC), Personal Competence (PC), Interpersonal Competence (IpC), and Project Management Competence (PMC). Results revealed significant gaps between current and expected levels of TC across all dimensions (p<0.001), with the largest disparities observed in LC and SC. Correlation analysis demonstrated strong interdependencies among all dimensions, and CT emerges as a central connector linking SC, LC, and IC. CT also showed strong correlations with TK, ThC, TechC, and PMC, and moderate correlations with PC and IpC. The findings validated the holistic nature of TC and highlighted the urgency to integrate human-centric communication with digital literacy in translator training. Based on empirical survey results and relevant theories, an Integrated Digital and Human Communication Platform is proposed to address the needs of TC development. The study enriched the literature on TC models and provided valuable insights for translation education.
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Keywords
Translation Competence, Foreign Language Education, Development Needs, AI, Critical Thinking
Supporting Agencies
No funding sources declared.
References
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Kiraly, D. C. (2000). A Social Constructivist Approach to Translator Education: Empowerment from Theory to Practice (1st ed.). Routledge. DOI: https://doi.org/10.4324/9781315760186
Krejcie, R. V., & Morgan, D. W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30: 607-610.
Liu, H. (2019). Teaching models of translation courses aiming at fostering critical thinking skills. In C. Ma (Ed.), 2019 International Conference on Advanced Education, Service and Management (Vol. 3, pp. 404-407). The Academy of Engineering and Education.
Mah, D. K. & Groß, N. (2024). Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21, 58. DOI: https://doi.org/10.1186/s41239-024-00490-1
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Mou, X. (2022). Research on the cultivation of technical competence of translation talents in China in the era of artificial intelligence. Journal of Shandong University of Technology (Social Sciences Edition), 38(03), 64–69.
Neubert, A. (1994). Competence in translation: A complex skill, how to study and how to teach it. In M. Snell-Hornby, F. Pöchhacker & K. Kaindl. Translation Studies: An Interdiscipline, Amsterdam/Philadelphia, John Benjamins, pp. 411-420.
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O’Dea, X. (2024). Generative AI: Is it a paradigm shift for higher education? Studies in Higher Education, 49(5), 811–816. DOI: https://doi.org/10.1080/03075079.2024.2332944
Owidi, S. & Lyanda, J. (2025). Integrating Artificial Intelligence in Micro Teaching: The Role of ChatGPT for Customized Feedback and Interactive Learning. International Journal of Research in Social Sciences and Humanities. 12. 1-10. DOI: https://doi.org/10.5281/zenodo.15130275
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Wu, Y. (2024). Critical Thinking Pedagogics Design in an Era of ChatGPT and Other AI Tools — Shifting from Teaching “What” to Teaching “Why” and “How”. Journal of Education and Development. 8(1): 1-10. DOI: https://doi.org/10.20849/jed.v8i1.1404
Xiao, Y., & Wei, L. (2021). CAT+MT+PE: A model for translation teaching. Chinese Journal of Applied Linguistics, 44(4), 512–529.
Xu H. & Hu, Y. (2022). Re-exploration of Translation Capabilities in the Era of Artificial Intelligence and Its Implications for the Cultivation of Translation Talents in China. Translation Teaching and Research, 2022(01):56-65.
Yang, Y. & Wang, X. (2023). Predicting student translators’ performance in machine translation post-editing: interplay of self-regulation, critical thinking, and motivation. Interactive Learning Environments, 31(1), 340-354. DOI: https://doi.org/10.1080/10494820.2020.1786407
Zhang, J. & Qian, H. (2023). The impact of machine translation on the translation quality of undergraduate translation students. Proceedings of Machine Translation Summit XIX, 2, 99-108. Available at: https://aclanthology.org/2023.mtsummit-users.9
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Albir, A. H. (2017). Researching Translation Competence by PACTE Group. John Benjamins. DOI: https://doi.org/10.1075/btl.127
ATC (2023). UK Language Services Industry Survey and Report 2023 [PDF]. ATC (Association of Translation Companies). Available at: https://atc.org.uk/2023-uk-language-services-industry-survey-report-is-out/
Barnlund, D. C. (2008). A transactional model of communication. In C. D. Mortensen (Ed.), Communication theory (2nd ed., pp. 47–57). Routledge.
Belshaw, D. (2011). What is digital literacy? A pragmatic investigation (Doctoral dissertation, Durham University). Available at: https://clalliance.org/wp-content/uploads/files/doug-belshaw-edd-thesis-final.pdf
Borge, M., Smith, B. K., & Aldemir, T. (2024). Using generative AI as a simulation to support higher-order thinking. International Journal of computer-Supported Collaborative Learning, 19(4), 479–532. DOI: https://doi.org/10.1007/s11412-024-09437-0
Cheng, S. (2022). Exploring the role of translators’ emotion regulation and critical thinking ability in translation performance. Frontiers in Psychology, 13, 1037829. DOI: https://doi.org/10.3389/fpsyg.2022.1037829
China Translation Proficiency Assessment Standards (2022). edo202204201052162122385.pdf (catticenter.com)
Chiu, T. K. (2024). Future research recommendations for transforming higher education with generative AI. Computers and Education: Artificial Intelligence, 6, 100197. DOI: https://doi.org/10.1016/j.caeai.2023.100197
Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2023). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1). DOI: https://doi.org/10.1080/2331186X.2023.2290342
DeVellis, R. F. & Thorpe, C. T. (2021). Scale development: Theory and Applications. Sage publications.
ELIS (2024). European language industry survey 2024 [PDF]. ELIS (European Language Industry Survey). P. 31. Available at: https://elis-survey.org/wp-content/uploads/2024/03/ELIS-2024-Report.pdf
EMT (2017). The European Master’s in Translation Competence Framework 2017 [PDF]. EuropeanCommission. P. 9. Available at: https://commission.europa.eu/system/files/2018-02/emt_competence_fwk_2017_en_web.pdf
EMT (2022). European Master’s in Translation Competence Framework, 2022. European Master’s in Translation (EMT) explained - European Commission (europa.eu). Available at: https://commission.europa.eu/system/files/2022-11/emt_competence_fwk_2022_en.pdf
Esfandiari, M. R., Shokrpour, N., & Rahimi, F. (2019). An Evaluation of the EMT: Compatibility with the Professional Translator’s Needs. Cogent Arts & Humanities, 6 (1): 1601055. DOI: https://doi.org/10.1080/23311983.2019.1601055.
Fahim, M. & Parham, F. (2013). The Relationship Between Critical Thinking and Translation Quality. Translation Studies. 11. 10-22.
Feng, Q. G. & Liu, M. (2018). Post-editing competence model. Foreign Language World, 3:55-61.
Froeliger, N., Krause, A., Salmi, L. (2022). Institutional translation-EMT Competence Framework and beyond. In Svoboda, T., Biel, Ł., & Sosoni, V. (Eds.). Institutional Translator Training (1st ed.). Routledge. DOI: https://doi.org/10.4324/9781003225249
Gervais, J. (2016). The operational definition of competency-based education. The Journal of Competency-Based Education, 1(2), 98-106. DOI: https://doi.org/10.1002/cbe2.1011
Ghaemi, H., & Sadoughvanini, S. (2020). The relationship between translation competence and higher-order thinking skills of novice translators. Athens Journal of Philology, 7(4), 273-288. DOI: https://doi.org/10.30958/ajp.7-4-3
Göpferich, S. (2009). Towards a model of translation competence and its acquisition: the longitudinal study TransComp. Copenhagen studies in language, 11-37. P. 21
Hair, J. F., Black, W. C., Babin, B. J., Anderson, R. E., & Tatham, R. L. (2010). Multivariate data analysis (7th ed.). Upper Saddle River, NJ: Prentice Hall.
Hatim, B., & Mason, I. (1990). Discourse and the Translator. London: Longman. P. 223.
Hauer, J. & Quill, T. (2011). Educational needs assessment, development of learning objectives and choosing a teaching approach, Journal of Palliative Medicine, 14 (4): 503-508.
Hazaea, A. & Qassem, M. (2024). Translation Competence in Translator Training Programs at Saudi Universities: Empirical Study. Open Education Studies, 6(1), 20240029. DOI: https://doi.org/10.1515/edu-2024-0029
ISO (2015). ISO 17100 Translation services-requirements for translation services [PDF]. Available at: https://cdn.standards.iteh.ai/samples/59149/351fb68fbff04254a83e6a903688fec9/ISO-17100-2015.pdf
Khoshafah, F. (2023). ChatGPT for Arabic-English Translation: Evaluating the Accuracy, PREPRINT (Version 1) retrieved at 7, 20,2025, Research Square. DOI: https://doi.org/10.21203/rs.3.rs-2814154/v1.
Kiraly, D. (1995). Process Pathways to Translation: Pedagogy and Process. Kent (Ohio): The Kent State University Press.
Kiraly, D. C. (2000). A Social Constructivist Approach to Translator Education: Empowerment from Theory to Practice (1st ed.). Routledge. DOI: https://doi.org/10.4324/9781315760186
Krejcie, R. V., & Morgan, D. W. (1970). Determining Sample Size for Research Activities. Educational and Psychological Measurement, 30: 607-610.
Liu, H. (2019). Teaching models of translation courses aiming at fostering critical thinking skills. In C. Ma (Ed.), 2019 International Conference on Advanced Education, Service and Management (Vol. 3, pp. 404-407). The Academy of Engineering and Education.
Mah, D. K. & Groß, N. (2024). Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21, 58. DOI: https://doi.org/10.1186/s41239-024-00490-1
Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. Teachers College Record, 108(6), 1017–1054.
Mou, X. (2022). Research on the cultivation of technical competence of translation talents in China in the era of artificial intelligence. Journal of Shandong University of Technology (Social Sciences Edition), 38(03), 64–69.
Neubert, A. (1994). Competence in translation: A complex skill, how to study and how to teach it. In M. Snell-Hornby, F. Pöchhacker & K. Kaindl. Translation Studies: An Interdiscipline, Amsterdam/Philadelphia, John Benjamins, pp. 411-420.
Neubert, A. (2000). Competence in Language, in Languages and in Translation. In Schäffner, C. & Adab, B. (eds.). Developing Translation Competence. Amsterdam/Philadelphia, John Benjamins, pp. 3-18. DOI: https://doi.org/10.1075/btl.38.03neu.
O’Dea, X. (2024). Generative AI: Is it a paradigm shift for higher education? Studies in Higher Education, 49(5), 811–816. DOI: https://doi.org/10.1080/03075079.2024.2332944
Owidi, S. & Lyanda, J. (2025). Integrating Artificial Intelligence in Micro Teaching: The Role of ChatGPT for Customized Feedback and Interactive Learning. International Journal of Research in Social Sciences and Humanities. 12. 1-10. DOI: https://doi.org/10.5281/zenodo.15130275
PACTE Group (2003). Building a translation competence model. Meta, 48(4), 609–632.
PACTE Group (2005). Investigating translation competence: conceptual and methodological issues. Meta 50(2), 609–619. DOI: https://doi.org/10.7202/011004ar
PACTE (2009). Results of the validation of the PACTE translation competence model: Acceptability and decision making. Across Languages and Cultures 10: 207–30.
Pallant, J. (2015). SPSS Survival Manual. Open University Press, Berkshire.
Panit, S., & Naneta, K. (2025). Over-reliance on AI and critical thinking decline in translation students. Journal of Second Language Writing, 62, 101234.
Pintrich, P. R., Smith, D., Garcia, T., & McKeachie, W. (1991). A manual for the use of the motivated strategies for learning questionnaire (MSLQ). The University of Michigan. Available at: https://www.researchgate.net/publication/271429287_A_Manual_for_the_Use_of_the_Motivated_Strategies_for_Learning_Questionnaire_MSLQ
Prieto Ramos, F. (2024). Revisiting translator competence in the age of artificial intelligence: the case of legal and institutional translation. The Interpreter and Translator Trainer, 18(2), 148–173. DOI: https://doi.org/10.1080/1750399X.2024.2344942
Ramírez-Polo, L. & Vargas-Sierra, C. (2023). Translation Technology and Ethical Competence: An Analysis and Proposal for Translators’ Training. Languages 8:93. DOI: https://doi.org/10.3390/languages8020093
Salamah, D. (2022). Translation competence and the translation job market in Saudi Arabia: investigating recruitment practices and job-market readiness. Saudi Journal of Language Studies, 2 (4): 236–258. DOI: https://doi.org/10.1108/SJLS-08-2022-0064
Sardi, J., Darmansyah, Candra, O., Yuliana, D. F., Habibullah, Yanto, D. T. P., & Eliza, F. (2025). How Generative AI Influences Students’ Self-Regulated Learning and Critical Thinking Skills? A Systematic Review. International Journal of Engineering Pedagogy (iJEP), 15(1), pp. 94–108. DOI: https://doi.org/10.3991/ijep.v15i1.53379
Shahini, A. (2025). Constructivism in Language Learning. In: Language Learning Theories. Palgrave Macmillan, Cham. DOI: https://doi.org/10.1007/978-3-031-92210-7_4
Škobo, M., & Petričević, V. (2023). Navigating the challenges and opportunities of literary translation in the age of AI: Striking a balance between human expertise and machine power. Društvene i Humanističke Studije (Social and Humanistic Studies), 8(2 (23)), 317–336.
TAC (2024). the 2023 China Translation and Language Services Industry Development Report [PDF]. TAC (Translators Association of China). Available at: https://www.tac-online.org.cn/node_1015758.html
Walsh, C. (2016). Digital Literacies. In: Peters, M. (eds) Encyclopedia of Educational Philosophy and Theory. Springer, Singapore. DOI: https://doi.org/10.1007/978-981-287-532-7_110-1
Wang L., & Wang, X. (2023). The Study on the Training Model of Machine Translation Post-Editing Competence in the Era of ChatGPT. Technology Enhanced Foreign Language Education, (04), 16-23+115. DOI: https://doi.org/10.20139/j.issn.1001-5795.2023.04.003
Wang, X., & Yang, W. (2023). An empirical study on developing higher-order thinking in translation technology teaching: Analysis of cognitive, behavioral and affective features. Foreign Language World, (04),16-24. DOI: https://doi.org/CNKI:SUN:WYJY.0.2023-04-003
Wesselink, R., Biemans, H., Gulikers, J., Mulder, M. (2017). Models and Principles for Designing Competence-based Curricula, Teaching, Learning and Assessment. In: Mulder, M. (eds) Competence-based Vocational and Professional Education. Technical and Vocational Education and Training: Issues, Concerns and Prospects, vol 23. Springer, Cham. DOI: https://doi.org/10.1007/978-3-319-41713-4_25
Wu, W. Fan, W. & Peng, R. (2013). Analysis of Dimensions and Evaluation Scales of Cross-Cultural Competence of Chinese College Students. Foreign Language Teaching and Research, 45(04):581-592+641.
Wu, Y. (2024). Critical Thinking Pedagogics Design in an Era of ChatGPT and Other AI Tools — Shifting from Teaching “What” to Teaching “Why” and “How”. Journal of Education and Development. 8(1): 1-10. DOI: https://doi.org/10.20849/jed.v8i1.1404
Xiao, Y., & Wei, L. (2021). CAT+MT+PE: A model for translation teaching. Chinese Journal of Applied Linguistics, 44(4), 512–529.
Xu H. & Hu, Y. (2022). Re-exploration of Translation Capabilities in the Era of Artificial Intelligence and Its Implications for the Cultivation of Translation Talents in China. Translation Teaching and Research, 2022(01):56-65.
Yang, Y. & Wang, X. (2023). Predicting student translators’ performance in machine translation post-editing: interplay of self-regulation, critical thinking, and motivation. Interactive Learning Environments, 31(1), 340-354. DOI: https://doi.org/10.1080/10494820.2020.1786407
Zhang, J. & Qian, H. (2023). The impact of machine translation on the translation quality of undergraduate translation students. Proceedings of Machine Translation Summit XIX, 2, 99-108. Available at: https://aclanthology.org/2023.mtsummit-users.9
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How to Cite
Liang, M., Panyanuwat, A., Rupavijetra, P., & Lomlai, S. (2025). Assessment of Translation Competence Development Needs of Foreign Language Majors at Guangxi University of Foreign Languages. Science Insights Education Frontiers, 30(2), 4927–4950. https://doi.org/10.15354/sief.25.or837
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