Translator education as a collaborative quest for insights into the re-positioning of the human translator (educator) in the age of machine translation: the results of a learning experiment

References

• Alimen, N., and S. Öner Bulut. 2020. “Çevirinin Teknolojikleşmesi Bağlamında İnsan Çevirmenin Rollerini Yeniden Düşünmek: Çevirmen Eğitiminde Teknik Metin Yazarlığı.” Turkish Studies 15 (3): 1047–1062. https://doi.org/10.47845/TurkishStudies.45679.
   Google Scholar
• Cadwell, P., S. O’Brien, and C. S. C. Teixeira. 2018. “Resistance and Accommodation: Factors for the (Non-) Adoption of Machine Translation Among Professional Translators.” Perspectives 26 (3): 301–321. https://doi.org/10.1080/0907676X.2017.1337210.
   Web of Science ®Google Scholar
• Calude, A. S. 2003. “Machine Translation of Various Text Genres.” Te Reo 46:67–94. http://140.234.252.185/c/articles/15642464/machine-translation-various-text-genres.
   Google Scholar
• Castilho, S. 2021. “Towards Document-Level Human MT Evaluation: On the Issues of Annotator Agreement, Effort and Misevaluation.” In Proceedings of the Workshop on Human Evaluation of NLP Systems (HumEval), Online, 34–45.
   Google Scholar
• Castilho, S., M. Popović, and A. Way. 2020. “On Context Span Needed for Machine Translation Evaluation.” In Proceedings of the 12thLanguage Resources and Evaluation Conference, Marseille, France, 3735–3742.
   Google Scholar
• Christian, B. 2011. The Most Human Human: A Defence of Humanity in the Age of the Computer. London: Viking.
   Google Scholar
• Doherty, S., and D. Kenny. 2014. “The Design and Evaluation of a Statistical Machine Translation Syllabus for Translation Students.” The Interpreter and Translator Trainer 8 (2): 295–315. https://doi.org/10.1080/1750399X.2014.937571.
   Web of Science ®Google Scholar
• Doherty, S., J. Moorkens, F. Gaspari, and C. Sheila. 2018. “On Education and Training in Translation Quality Assessment.” In Translation Quality Assessment, edited by J. Moorkens, S. Castilho, F. Gaspari, and S. Doherty, 95–106. Cham, Switzerland: Springer. https://doi.org/10.1007/978-3-319-91241-7_5.
   Google Scholar
• Engeström, Y., and A. Sannino. 2010. “Studies of Expansive Learning: Foundations, Findings and Future Challenges.” Educational Research Review 5 (1): 1–24. https://doi.org/10.1016/j.edurev.2009.12.002.
   Web of Science ®Google Scholar
• Flanagan, M., and T. P. Christensen. 2014. “Testing Post-Editing Guidelines: How Translation Trainees Interpret Them and How to Tailor Them for Translator Training Purposes.” The Interpreter and Translator Trainer 8 (2): 257–275. https://doi.org/10.1080/1750399X.2014.936111.
   Web of Science ®Google Scholar
• Göpferich, S. 1995. Textsorten in Naturwissenschaften und Technik. Pragmatische Typologie - Kontrastierung - Translation. Tübingen, Germany: Gunter Narr.
   Google Scholar
• Görög, A. 2014. “Quantifying and Benchmarking Quality: The TAUS Dynamic Quality Framework.” Tradumàtica tecnologies de la traducció 12 (12): 443–454. https://doi.org/10.5565/REV%2FTRADUMATICA.66.
   Google Scholar
• Haro-Soler, M. M., and D. Kiraly. 2019. “Exploring Self-Efficacy Beliefs in Symbiotic Collaboration with Students: An Action Research Project.” The Interpreter and Translator Trainer 13 (3): 255–270. https://doi.org/10.1080/1750399X.2019.1656405.
   Web of Science ®Google Scholar
• Holmes, J. S. 1972/2000. “The Name and Nature of Translation Studies.” In The Translation Studies Reader, edited by L. Venuti, 172–185. 2nd ed. London and New York: Routledge.
   Google Scholar
• Hönig, H. G. 1997. “Translating: The Constructive Way.” Ilha Do Desterro A Journal of English Language, Literatures in English and Cultural Studies 33:11–23. https://periodicos.ufsc.br/index.php/desterro/issue/view/635.
   Google Scholar
• Jones, M. R. 1999. “Information Systems and the Double Mangle: Steering a Course Between the Scylla of Embedded Structure and the Charybdis of Strong Symmetry.” In Information Systems: Current Issues and Future Changes, edited by T. J. Larsen, L. Levine, and J. I. DeGross, 287–302. Laxenburg, Austria: International Federation for Information Processing.
   Google Scholar
• Kenny, D., and S. Doherty. 2014. “Statistical Machine Translation in the Translation Curriculum: Overcoming Obstacles and Empowering Translators.” The Interpreter and Translator Trainer 8 (2): 276–294. https://doi.org/10.1080/1750399X.2014.936112.
   Web of Science ®Google Scholar
• Kiraly, D. C. 1990. “Toward a Systematic Approach to Translation Skills Instruction.” PhD diss., University of Illinois.
   Google Scholar
• Kiraly, D. C. 2000. A Social Constructivist Approach to Translator Education: Empowerment from Theory to Practice. Manchester: St. Jerome.
   Google Scholar
• Latorraca, R. 2018. “Think Aloud as a Tool for Implementing Observational Learning in the Translation Class.” Perspectives 26 (5): 708–724. https://doi.org/10.1080/0907676X.2017.1407804.
   Web of Science ®Google Scholar
• Li, D. 2011. “Think-Aloud Teaching in Translation Class: Implications from TAPs Translation Research.” Perspectives 19 (2): 109–122. https://doi.org/10.1080/0907676X.2010.506955.
   Web of Science ®Google Scholar
• Massey, G. 2021. “Re-Framing Conceptual Metaphor Translation Research in the Age of Neural Machine Translation: Investigating Translators’ Added Value with Products and Processes.” Training Language and Culture 5 (1): 37–56. https://doi.org/10.22363/2521-442X-2021-5-1-37-56.
   Google Scholar
• Massey, G., and D. Kiraly. 2019. “The Future of Translator Education: A Dialogue.” Cultus: The Journal of Intercultural Mediation and Communication 12:15–34. https://www.cultusjournal.com/files/Archives/Cultus_2019_12_002_Kiraly_Massey.pdf.
   Google Scholar
• Mellinger, C. D. 2017. “Translators and Machine Translation: Knowledge and Skills Gaps in Translator Pedagogy.” The Interpreter and Translator Trainer 11 (4): 280–293. https://doi.org/10.1080/1750399X.2017.1359760.
   Web of Science ®Google Scholar
• Mellinger, C. D. 2019. “Metacognition and Self-Assessment in Specialized Translation Education: Task Awareness and Metacognitive Bundling.” Perspectives 27 (4): 604–621. https://doi.org/10.1080/0907676X.2019.1566390.
   Web of Science ®Google Scholar
• Mercader-Alarcón, J., and F. Sánchez-Martínez. 2016. “Analysis of Translation Errors and Evaluation of Pre-Editing Rules for the Translation of English News Texts into Spanish with Lucy LT.” Tradumàtica tecnologies de la traducció 14 (14): 172–186. https://doi.org/10.5565/rev/tradumatica.164.
   Google Scholar
• Moorkens, J. 2018. “What to Expect from Neural Machine Translation: A Practical In-Class Translation Evaluation Exercise.” The Interpreter and Translator Trainer 12 (4): 375–387. https://doi.org/10.1080/1750399X.2018.1501639.
   Web of Science ®Google Scholar
• Nitzke, J., S. Hansen-Schirra, and C. Canfora. 2019. “Risk Management and Post-Editing Competence.” Journal of Specialised Translation 31:239–259. https://jostrans.org/issue31/issue31_toc.php.
   Google Scholar
• O’Brien, S. 2012. “Translation as Human-Computer Interaction.” Translation Spaces 1:101–122. https://doi.org/10.1075/ts.1.05obr.
   Google Scholar
• Olohan, M. 2007. “Economic Trends and Developments in the Translation Industry.” The Interpreter and Translator Trainer 1 (1): 37–63. https://doi.org/10.1080/1750399X.2007.10798749.
   Web of Science ®Google Scholar
• Olohan, M. 2011. “Translators and Translation Technology: The Dance of Agency.” Translation Studies 4 (3): 342–357. https://doi.org/10.1080/14781700.2011.589656.
   Web of Science ®Google Scholar
• Öner, I. 2018. “Why Technical Writing is One of the Basic Courses in Translation Studies.” Intelligent Information Blog, January 31. Accessed May 15, 2022. https://intelligent-information.blog/en/why-technical-writing-is-one-of-the-basic-courses-in-translation-studies/.
   Google Scholar
• Öner Bulut, S. 2019. “Integrating Machine Translation into Translator Training: Towards ‘Human Translator Competence’?” transLogos Translation Studies Journal 2 (2): 1–26. https://doi.org/10.29228/transLogos.11.
   Google Scholar
• Öner, I., and S. Öner Bulut. 2021. “Post-Editing Oriented Human Quality Evaluation of Neural Machine Translation in Translator Training: A Study on Perceived Difficulties and Benefits.” transLogos Translation Studies Journal 4 (1): 100–124. https://doi.org/10.29228/transLogos.33.
   Google Scholar
• Pickering, A. 1993. “The Mangle of Practice: Agency and Emergence in the Sociology of Science.” American Journal of Sociology 99 (3): 559–589. https://doi.org/10.1086/230316.
   Web of Science ®Google Scholar
• Pickering, A. 2008. “New Ontologies.” In The Mangle in Practice. Science, Society and Becoming, edited by A. Pickering and K. Guzik, 1–14. Durham, NC: Duke University Press. https://doi.org/10.2307/j.ctv11smg5w.4.
   Google Scholar
• Pym, A. 2019. “How Automation Through Neural Machine Translation Might Change the Skill Sets of Translators.” Draft Written as Part of the Project Language Competence and Work (RecerCaixa 2016ACUP00020), 2017–2019. Accessed May 1, 2020. https://www.academia.edu/40200406/How_automation_through_neural_machine_translation_might_change_the_skill_sets_of_translators.
   Google Scholar
• Ruokonen, M., and K. Koskinen. 2017. “Dancing with Technology: Translators’ Narratives on the Dance of Human and Machinic Agency in Translation Work.” The Translator 23 (3): 310–323. https://doi.org/10.1080/13556509.2017.1301846.
   Web of Science ®Google Scholar
• Vermeer, H. J. 2000. “Skopos and Commission in Translational Action.” In The Translation Studies Reader, edited by L. Venuti, 221–232. London and New York: Routledge.
   Google Scholar