Integrating AI into Translation Pedagogy: University Lecturers’ Readiness in Indonesia and Timor-Leste

Authors

  • Jafar Sodiq Universitas PGRI Semarang
  • Theresia Cicik Sophia Budiman Universitas PGRI Semarang Indonesia
  • Arso Setyaji Universitas PGRI Semarang Indonesia
  • Zainal Arifin Universitas PGRI Semarang Indonesia
  • Joaquina Marques Soares Dili Institute of Technology

DOI:

https://doi.org/10.24903/sj.v11i2.2421

Keywords:

artificial intelligence, higher education, readiness for integration, qualitative research, translation pedagogy

Abstract

Background:

The increasing use of artificial intelligence (AI) in translation technologies is transforming translation pedagogy and creating new opportunities and challenges for translation pedagogy and creating new opportunities and challenges for translator education. As AI-assisted tools become increasingly integrated into professional translation practices, understanding lecturers’ readiness to incorporate AI into teaching becomes essential for effective and responsible implementation.

Methodology:

This study employed a qualitative descriptive design involving six university lecturers as purposive sampling who can teach translation courses in Indonesia and Timor-Leste. Data were collected through semi-structured interviews and analyzed thematically using Maxqda 2024.

Findings:

The findings revealed four interconnected dimensions of lecturers’ readiness for AI integration: pedagogical perception, ethical-professional awareness, and institutional ecosystem support. Participants generally demonstrated positive attitudes toward AI and moderate to high technological confidence. However, concerns regarding translation accuracy, overreliance on AI-generated outputs, academic integrity, and ethical responsibility remained evident.

Conclusion:

Lecturers’ readiness for AI integration extends beyond technological competence and involves pedagogical adaptation, ethical literacy, and institutional support. Effective implementation requires balanced integration that promotes critical engagement with AI while preserving core translation competencies.

Originality:

This study proposes an AI Readiness Framework for Translation Pedagogy that conceptualizes readiness as a multidimensional interaction among pedagogical, technological, ethical, and institutional factors. The framework contributes to the growing literature on AI-assisted translation education by foregrounding lecturers’ perspectives.

References

Abdalgane, M., & Othman, K. A. J. (2023). Utilizing Artificial Intelligence Technologies in Saudi EFL Tertiary Level Classrooms. Journal of Intercultural Communication, 23(1), 92–99. https://doi.org/10.36923/jicc.v23i1.124

Albus, P., Vogt, A., & Seufert, T. (2021). Signaling in virtual reality influences learning outcome and cognitive load. Computers and Education, 166(April 2020), 104154. https://doi.org/10.1016/j.compedu.2021.104154

Alfadil, M. (2020). Effectiveness of virtual reality game in foreign language vocabulary acquisition. Computers and Education, 153. https://doi.org/10.1016/j.compedu.2020.103893

Ayuningrum, N. D., Ngazizah, N., & Ratnaningsih, A. (2024). The Effectiveness of Authentic Assessment Instrument Based on Higher Order Thinking Skills Integrated with Character Education. Journal of Innovation and Research in Primary Education, 3(1), 1–10. https://doi.org/10.56916/jirpe.v3i1.548

Baier, F., Decker, A.-T., Voss, T., Kleickmann, T., Klusmann, U., & Kunter, M. (2019). What makes a good teacher? The relative importance of mathematics teachers’ cognitive ability, personality, knowledge, beliefs, and motivation for instructional quality. British Journal of Educational Psychology, 89(4), 767–786. https://doi.org/10.1111/bjep.12256

Bowker, L. (2021). Machine translation use outside the language industries: a comparison of five delivery formats for machine translation literacy instruction. 25–36. https://doi.org/10.26615/978-954-452-071-7_004

Bowker, Lynne., & Ciro, J. Buitrago. (2019). Machine translation and global research: towards improved machine translation literacy in the scholarly community. Emerald Publishing Limited.

Cheng, M. (2022). Practical Exploration of English Translation Activity Courses in Colleges and Universities under the Background of Artificial Intelligence. Wireless Communications and Mobile Computing, 2022. https://doi.org/10.1155/2022/4547342

Daems, J., Vandepitte, S., Hartsuiker, R. J., & Macken, L. (2017). Identifying the machine translation error types with the greatest impact on post-editing effort. Frontiers in Psychology, 8(AUG). https://doi.org/10.3389/fpsyg.2017.01282

Ertmer, P. A., & Ottenbreit-Leftwich, A. T. (2010). Teacher technology changes: How knowledge, confidence, beliefs, and culture intersect. Journal of Research on Technology in Education, 42(3), 255–284. https://doi.org/10.1080/15391523.2010.10782551

Fagerlund, J., Palsa, L., & Mertala, P. (2025). Experts’ Problematizations of the Datafication of Education: A Narrative Analysis. https://doi.org/10.35542/osf.io/n3jrh_v1

Falempin, A., & Ranadireksa, D. (2024). Human vs. Machine: The Future of Translation in an AI-Driven World (pp. 177–183). https://doi.org/10.2991/978-94-6463-618-5_19

Farmasari, S., Wardana, L. A., Baharuddin, & Suryaningsih, H. (2026). Predicting Future Identity of English for Young Learner (EYL) Teachers: Investigating How Coursework Shapes Pre-Service Teachers’ Identities and Teaching Readiness. Script Journal: Journal of Linguistics and English Teaching, 11(1), 138–153. https://doi.org/10.24903/sj.v11i1.2344

Floridi, L., & Chiriatti, M. (2020). GPT 3 : Its Nature, Scope, Limits, and Consequences. Minds and Machines, 30(4), 681–694. https://doi.org/10.1007/s11023-020-09548-1

Gayed, J. M., Carlon, M. K. J., Oriola, A. M., & Cross, J. S. (2022). Exploring an AI-based writing Assistant’s impact on English language learners. Computers and Education: Artificial Intelligence, 3. https://doi.org/10.1016/j.caeai.2022.100055

Göpferich, S. (2009). Towards a model of translation competence and its acquisition: the longitudinal study TransComp.

Hamid, S. F., Shopia, K., & Isnaniah, I. (2024). Developing TPACK Based Assessment Instrument for Teaching Practice of English Education Students. Journal of English Language and Language Teaching, 8(2), 39–56. https://doi.org/10.36597/jellt.v8i2.18125

Huang, X., Zou, D., Cheng, G., & Xie, H. (2021). A systematic review of AR and VR enhanced language learning. Sustainability (Switzerland), 13(9), 1–28. https://doi.org/10.3390/su13094639

Jia, Y., Yang, X., & Cui, Q. (2024). Research on the Role of Artificial Intelligence in the Core of Intelligent Translation Systems. Procedia Computer Science, 243, 585–592. https://doi.org/10.1016/j.procs.2024.09.071

Kadel, P. B. (2020). Teachers’ Perceptions of Critical Pedagogy in English Language Teaching Classroom. Journal of NELTA, 25(1–2), 179–190. https://doi.org/10.3126/nelta.v25i1-2.49740

Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. In Learning and Individual Differences (Vol. 103). Elsevier Ltd. https://doi.org/10.1016/j.lindif.2023.102274

Kenny, D. (2022a). Machine translation for everyone: Empowering users in the age of artificial intelligence. In Machine translation for everyone: Empowering users in the age of artificial intelligence. Language Science Press. https://doi.org/10.5281/zenodo.6653406

Kenny, D. (2022b). Machine translation for everyone Empowering users in the age of artificial intelligence Translation and Multilingual Natural Language Processing 18. https://langsci-press.org/catalog/series/tmnlp

Kim, H. S., & Cha, Y. (2023). The Role of AI Translators on Reading Comprehension. Korean Journal of English Language and Linguistics, 23, 38–58. https://doi.org/10.15738/kjell.23.202301.38

Kiraly, D. C. (2017). A social constructivist approach to translator education: Empowerment from theory to practice. St. Jerome Publishing.

Kusmaryani, W., Ramli, & Winarno. (2026). Effectiveness of AI Speech Recognition on Students’ English Pronunciation. Script Journal: Journal of Linguistics and English Teaching, 11(1), 77–98. https://doi.org/10.24903/sj.v11i1.2282

Lee, Y. J., & Roger, P. (2023). Cross-platform language learning: A spatial perspective on narratives of language learning across digital platforms. System, 118, 103145. https://doi.org/10.1016/J.SYSTEM.2023.103145

Lin, Y. (2023). The relationship between machine translation and human translation in the era of artificial intelligence machine translation. Applied and Computational Engineering, 5(1), 133–138. https://doi.org/10.54254/2755-2721/5/20230547

Liu, D. (2016). The Reform and Innovation of English Course: A Coherent Whole of MOOC, Flipped Classroom and ESP. Procedia - Social and Behavioral Sciences, 232, 280–286. https://doi.org/10.1016/j.sbspro.2016.10.021

Liu, S., & Zhu, W. (2023). An Analysis of the Evaluation of the Translation Quality of Neural Machine Translation Application Systems an Analysis of the Evaluation of the Translation Quality of Neural Machine Translation Application Systems. Applied Artificial Intelligence, 37(1). https://doi.org/10.1080/08839514.2023.2214460

Lo, C. K., Hew, K. F., & Jong, M. S. yung. (2024). The influence of ChatGPT on student engagement: A systematic review and future research agenda. Computers and Education, 219. https://doi.org/10.1016/j.compedu.2024.105100

Luo, Y., & Day, M. J. (2026). Determinants of lecturer readiness to adopt generative AI in higher education: survey evidence from UTAUT and self-determination theory. Education and Information Technologies, 31(10), 3399–3430. https://doi.org/10.1007/s10639-026-13931-3

Machala, S., Chamier-Gliszczynski, N., & Królikowski, T. (2022). Application of AR/VR Technology in Industry 4.0. Procedia Computer Science, 207, 2984–2992. https://doi.org/10.1016/j.procs.2022.09.357

Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki. (2023). Exploring Artificial Intelligence in Academic Essay: Higher Education Student’s Perspective. International Journal of Educational Research Open, 5. https://doi.org/10.1016/j.ijedro.2023.100296

Milli, S., Carroll, M., Wang, Y., Pandey, S., Zhao, S., & Dragan, A. D. (2025). Engagement, user satisfaction, and the amplification of divisive content on social media. PNAS Nexus, 4(3). https://doi.org/10.1093/pnasnexus/pgaf062

Mishra, P., & Koehler, M. J. (2006). Technological pedagogical content knowledge: A framework for teacher knowledge. In Teachers College Record (Vol. 108, Number 6, pp. 1017–1054). Teachers College, Columbia University. https://doi.org/10.1111/j.1467-9620.2006.00684.x

Mohamed, Y. A., Khanan, A., Bashir, M., Mohamed, A. H. H. M., Adiel, M. A. E., & Elsadig, M. A. (2024). The Impact of Artificial Intelligence on Language Translation: A Review. IEEE Access, 12, 25553–25579. https://doi.org/10.1109/ACCESS.2024.3366802

Moneus, A. M., & Sahari, Y. (2024). Artificial intelligence and human translation: A contrastive study based on legal texts. Heliyon, 10(6). https://doi.org/10.1016/j.heliyon.2024.e28106

Namaziandost, E. (2025). Integrating flipped learning in AI-enhanced language learning: Mapping the effects on metacognitive awareness, writing development, and foreign language learning boredom. Computers and Education: Artificial Intelligence, 9. https://doi.org/10.1016/j.caeai.2025.100446

Napu, N., Pakaya, U., Hanafi, H., Otoluwa, M. H., & Abduh, A. (2026). A Bibliometric Analysis of Translation Studies in Indonesia: Mapping Trends and Research Trajectories. Script Journal: Journal of Linguistics and English Teaching, 11(1), 154–171. https://doi.org/10.24903/sj.v11i1.2342

Nisiforou, E., & Kosmas, P. (2025). Assessing Institutional Readiness for Emerging Technologies Integration in Higher Education Assessing Institutional Readiness for Emerging Technologies Integration in Higher Education. (January 2024). https://doi.org/10.70725/441907jrwrsw

O’Brien, S. (2012). Translation as human–computer interaction. Translation Spaces, 1, 101–122. https://doi.org/10.1075/ts.1.05obr

Ottenbreit-Leftwich, A. T., Glazewski, K. D., Newby, T. J., & Ertmer, P. A. (2010). Teacher value beliefs associated with using technology: Addressing professional and student needs. Computers and Education, 55(3), 1321–1335. https://doi.org/10.1016/j.compedu.2010.06.002

Patil, B. J. (2025). AI-Powered Translation- Advancements, Challenges, and Future Prospects. International Journal of English and Studies (IJOES).

Pym, A. (2019). How neural machine translation might change the work of professional translators. Translation in the Digital Era: Proceedings of the 17th International Conference on Translation, 1–13. https://doi.org/10.15290/lingdid.2025.29.18

Rico, C. (2022). The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs. 14(1), 177–197. https://doi.org/10.12807/ti.114201.2022.a010

Rico, C., & Pastor, D. G. (2022). The role of machine translation in translation education: A thematic analysis of translator educators’ beliefs. Translation and Interpreting, 14(1), 177–197. https://doi.org/10.12807/TI.114201.2022.A010

Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press.

Sánchez-Gijón, P., M. J., & W. A. (2019). Post-editing neural machine translation versus translation memory segments. Machine Translation, 33, 31–59. https://doi.org/10.1007/s10590-019-09232-x

Sánchez-Gijón, P., Moorkens, J., & Way, A. (2019). Post-editing neural machine translation versus translation memory segments. Machine Translation, 33(1–2), 31–59. https://doi.org/10.1007/s10590-019-09232-x

Savoldi, B., G. M., B. L., N. M., & T. M. (2021). Gender bias in machine translation. Transactions of the Association for Computational Linguistics, 9, 845–874. https://doi.org/10.1162/tacl_a_00401

Setyaji, A. (2019). Translation Analysis of Taxis in “The Old Man and the Sea” Novel (Systemic Functional Linguistics Approach). Theory and Practice in Language Studies 9(2), 245–254. http://dx.doi.org/10.17507/tpls.0902.16

Tondeur, J., Pareja Roblin, N., van Braak, J., Voogt, J., & Prestridge, S. (2017). Preparing beginning teachers for technology integration in education: ready for take-off? Technology, Pedagogy and Education, 26(2), 157–177. https://doi.org/10.1080/1475939X.2016.1193556

UNESCO. (2021). AI and education: Guidance for policymakers. UNESCO.

van Dijk, R., van der Valk, I. E., Deković, M., & Branje, S. (2020). A meta-analysis on interparental conflict, parenting, and child adjustment in divorced families: Examining mediation using meta-analytic structural equation models. Clinical Psychology Review, 79(October 2019), 101861. https://doi.org/10.1016/j.cpr.2020.101861

Vretos, N., Daras, P., Asteriadis, S., Hortal, E., Ghaleb, E., Spyrou, E., Leligou, H. C., Karkazis, P., Trakadas, P., & Assimakopoulos, K. (2019). Exploiting sensing devices availability in AR/VR deployments to foster engagement. Virtual Reality, 23(4), 399–410. https://doi.org/10.1007/s10055-018-0357-0

Yuan, H. (2025). From Data to Decisions based on AI-Driven Insights: Intelligent Evaluation of English Translation Pedagogy in Higher Education under Interval Complex Neutrosophic Set. In Higher Education under Interval Complex Neutrosophic Set Neutrosophic Sets and Systems (Vol. 83). https://doi.org/10.5281/zenodo.15200126

Yuxiu, Y. (2024). Application of translation technology based on AI in translation teaching. Systems and Soft Computing, 6. https://doi.org/10.1016/j.sasc.2024.200072

Zarrati, Z., Zohrabi, M., Abedini, H., & Xodabande, I. (2024). Learning academic vocabulary with digital flashcards: Comparing the outcomes from computers and smartphones. Social Sciences and Humanities Open, 9(November 2023), 100900. https://doi.org/10.1016/j.ssaho.2024.100900

Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? In International Journal of Educational Technology in Higher Education (Vol. 16, Number 1). Springer Netherlands. https://doi.org/10.1186/s41239-019-0171-0

Zhang, C., Zhang, C., Zheng, S., Qiao, Y., Li, C., Zhang, M., Dam, S. K., Thwal, C. M., Tun, Y. L., Huy, L. L., kim, D., Bae, S.-H., Lee, L.-H., Yang, Y., Shen, H. T., Kweon, I. S., & Hong, C. S. (2023). A Complete Survey on Generative AI (AIGC): Is ChatGPT from GPT-4 to GPT-5 All You Need? http://arxiv.org/abs/2303.11717

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2026-09-01

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