Postgraduate Course: Technology and Translation in the Workplace (CLLC11065)
Course Outline
| School | School of Literatures, Languages and Cultures |
College | College of Arts, Humanities and Social Sciences |
| Credit level (Normal year taken) | SCQF Level 11 (Postgraduate) |
Availability | Not available to visiting students |
| SCQF Credits | 20 |
ECTS Credits | 10 |
| Summary | The main goal of the Technology and Translation in the Workplace (TTW) course is to equip students with key technology skills required as professional linguists and to enable them to critically reflect on the uses and impacts of these technologies. Classes are practice-oriented with project-based translation exercises, group work and discussions. At the end of the course, students will have become familiar with a range of computer-assisted translation (CAT) tools and will have gained an understanding of the principles of machine translation (MT).
Students will also have acquired skills and knowledge required in a professional environment, including the development of techniques and resources for terminology management, quality assurance and machine translation post-editing. The course will also cover practical questions concerning the translation profession and related roles, for instance workflows, remuneration and networking, and address wider social and ethical issues affecting the industry. The practical work will be complemented by discussions of current research in the field. |
| Course description |
Week 1-2: Introduction to translation technology
These sessions introduce translation as a technology-based activity, providing an overview of computer-assisted translation (CAT) tools and machine translation (MT) systems.
Weeks 3-5 and 7-10: Using CAT tools
Students will work with different CAT tools used in the translation industry, such as Trados Studio and Wordfast. The sessions offer hands-on experience in using translation memory tools and include aspects such as terminology management, quality assurance, cloud-based tools and integrating machine translation. This will enable students to compare and evaluate the different tools and their features. Based on these practical exercises, we will critically examine wider issues such as the changing roles of the translator and different forms of collaboration.
Week 11: Translation technologies, sustainability and ethics
This session addresses key questions relating to the impact of machine translation and generative AI and looks to the future of the translation profession.
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Entry Requirements (not applicable to Visiting Students)
| Pre-requisites |
|
Co-requisites | |
| Prohibited Combinations | |
Other requirements | None |
Course Delivery Information
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| Academic year 2026/27, Not available to visiting students (SS1)
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Quota: 0 |
| Course Start |
Semester 1 |
Timetable |
Timetable |
| Learning and Teaching activities (Further Info) |
Total Hours:
200
(
Lecture Hours 10,
Seminar/Tutorial Hours 10,
Feedback/Feedforward Hours 4,
Other Study Hours 4,
Programme Level Learning and Teaching Hours 4,
Directed Learning and Independent Learning Hours
168 )
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| Additional Information (Learning and Teaching) |
Pre-recorded Lecture Hours 10
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| Assessment (Further Info) |
Written Exam
0 %,
Coursework
100 %,
Practical Exam
0 %
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| Additional Information (Assessment) |
Assessment: 100% Coursework
500-word essay (30%) on machine translation, due in Week 7
2000-word essay (70%) on CAT tools, due in Week 12
Mid-semester essay (500 words): meets LO1, LO3 and LO4
End-of-semester essay (2000 words): meets LO1, LO2 and LO4 |
| Feedback |
Not entered |
| No Exam Information |
Learning Outcomes
On completion of this course, the student will be able to:
- Demonstrate professional skills in the area of translation technology important for your future career as a translator (or in a related role).
- Demonstrate an understanding of the principal techniques and functions of translation memory tools (CAT tools) and how to apply these practically in the translation of a wide range of documents and formats.
- Demonstrate an understanding of current developments in machine translation/AI and reflect critically on the impact of such technologies, in connection with CAT tools and on their own.
- Reflect and comment on the advantages/disadvantages and overall impact of the widespread use of CAT tools and machine translation/AI on the workflow of translators, and on the translation industry more broadly.
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Reading List
Bowker, L., and Corpas Pastor, G. (2015) 'Translation Technology' in Mitkov, R. et al. (eds.) The Oxford Handbook of Computational Linguistics (2nd ed.) [Online]. Oxford: Oxford University Press.
Bowker, L. (2021) 'Translation Technology and Ethics' in Pokorn, N. K. & Koskinen, K. (eds.) The Routledge Handbook of Translation and Ethics. Abingdon: Routledge, 262-278.
Bowker, L. (2022) 'Computer-assisted Translation and Interpreting Tools' in Zanettin, F. and Rundle, C. (eds.) The Routledge Handbook of Translation and Methodology. London: Routledge. pp. 382-409.
Cabré, M. T. (2010) 'Terminology and Translation' in Gambier, Y. & van Doorslaer, L. (eds.) Handbook of Translation Studies Volume 1. Amsterdam, Philadelphia: John Benjamins, 356-365.
Chan, S. (2015) (ed.) The Routledge Encyclopedia of Translation Technology. London: Routledge.
Chan, S. (2017) The Future of Translation Technology: Towards a World without Babel, London: Routledge.
Doherty, S. (2016) The Impact of Translation Technologies on the Process and Product of Translation. International Journal of Communication, 10: 947-969.
Duoxiu, Q. (2015) 'Translation Technology in China' in Chan, S.-W. (ed.) The Routledge Encyclopedia of Translation Technology. Abingdon & New York: Routledge, 255-266
García, I. (2015) 'Computer-Aided Translation: Systems' in Chan, S.-W. (ed.) The Routledge Encyclopedia of Translation Technology. Abingdon & New York: Routledge, 68-87.
Gouadec, D. (2010) Translation as a Profession, Amsterdam: John Benjamins.
Kenny D. (2011) 'Electronic Tools and Resources for Translators' in Malmkjaer, K. and Windle, K. (eds.) The Oxford Handbook of Translation Studies. Oxford: Oxford University Press, 1-18.
Moorkens, J. (2018) What to Expect from Neural Machine Translation: a Practical In-class Translation Evaluation Exercise. The Interpreter and Translator Trainer. [Online] 12 (4), 375-387.
Muegge, U. (2012) The Silent Revolution: Cloud-based Translation Management Systems. tcworld Magazine [Online]. Available from: https://works.bepress.com/uwe_muegge/67/
Nunes Viera, L. (2019). 'Post-editing Machine Translation' in O'Hagan, M. (ed.) The Routledge Handbook of Translation and Technology [Online]. London: Routledge, 319-335.
O'Brien, S. et al. (2017) Irritating CAT Tool Features That Matter to Translators. Hermes - Journal of Language and Communication in Business, 56: 145-162.
O'Hagan, M. (2019). The Routledge Handbook of Translation and Technology [Online]. London: Routledge.
Quah, C. K. (2006) Translation and Technology. London: Palgrave Macmillan
Reinke, U. (2013) State of the Art in Translation Memory Technology. Translation: Computation, Corpora, Cognition. [Online].
Schäffner, C. (2020) 'Translators' Roles and Responsibilities' in Angelone, M., Ehrensberger-Dow, M. & Massey, G. (eds.) The Bloomsbury Companion to Language Industry Studies [Online]. London: Bloomsbury Academic, 63-90.
Schneider, D. et al. (2018) Translation Memories and the Translator: A Report on a User Survey. Babel, 64(5-6): 734-762.
Screen, B. A. (2016) What does Translation Memory do to Translation?: The Effect of Translation Memory Output on Specific Aspects of the Translation Process. The International Journal of Translation and Interpreting Research, 8 (1), 1-18.
Sun, Sanjun (2021) 'Measuring the User Experience of Computer-Aided Translation Systems: a comparative study' in Muñoz Martín, R., Sun, S. and Li, D. (eds.) Advances in Cognitive Translation Studies (New Frontiers in Translation Studies). Singapore: Springer. pp. 67-88.
van der Meer, J. (2020) 'Translation Technology - Past, Present and Future' in Angelone, M., Ehrensberger-Dow, M. & Massey, G. (eds.) The Bloomsbury Companion to Language Industry Studies [Online]. London: Bloomsbury Academic, 285-310.
Vieira, L.N., O¿Hagan, M. & O'Sullivan, C. (2021) Understanding the Societal Impacts of Machine Translation: a Critical Review of the Literature on Medical and Legal Use Cases. Information, Communication & Society. [Online] 24 (11), 1515-1532. Available from: doi:10.1080/1369118X.2020.1776370.
Way, A. (2019) 'Machine Translation: Where Are we at Today?' in Angelone, M., Ehrensberger-Dow, M. & Massey, G. (eds.) The Bloomsbury Companion to Language Industry Studies [Online]. London: Bloomsbury Academic, 311-332.
Zaretskaya A. et al. (2015). Integration of Machine Translation in CAT Tools: State of the Art, Evaluation and User Attitudes. SKASE Journal of Translation and Interpretation, 8(1): 76-88.
Zetzsche, J. (2019). 'Freelance Translators' Perspectives' in O'Hagan, M. (ed.) The Routledge Handbook of Translation and Technology [Online]. London: Routledge, 166-182. |
Additional Information
| Graduate Attributes and Skills |
Not entered |
| Keywords | Not entered |
Contacts
| Course organiser | Ms Karin Bosshard
Tel:
Email: k.bosshard@ed.ac.uk |
Course secretary | Mrs Lina Gordyshevskaya
Tel:
Email: pgordysh@ed.ac.uk |
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