Volume 3, Issue 2
  • ISSN 2542-5277
  • E-ISSN: 2542-5285
Buy:$35.00 + Taxes



MT literacy means knowing how MT works, how the technology can be useful in a particular context, and what the implications are of using it for various purposes. As MT usage grows, the necessity for MT literacy also grows. This knowledge forms part of the greater need for digital literacies. In this contribution, we relate MT literacy to the concept of cognitive load in professional translation production and in translator training scenarios. We then move beyond the sphere of translation studies to examine other use-case settings—crisis communication, academic writing and patent publishing—to consider how MT can offer solutions and how MT literacy can impact cognitively in those settings. We discuss how training in MT literacy can empower language professionals and present two proposals for course content designed for MT users in other sectors.


Article metrics loading...

Loading full text...

Full text loading...


  1. Alexander, David , and Gianluca Pescaroli
    2019 “The Role of Translators and Interpreters in Cascading Crises and Disasters: Towards a framework for confronting the challenges.” Disaster Prevention and Management29 (1): 144–156. doi:  10.1108/DPM‑12‑2018‑0382
    https://doi.org/10.1108/DPM-12-2018-0382 [Google Scholar]
  2. Bayer-Hohenwarter, Gerrit
    2012Translatorische Kreativität: Definition—Messung—Entwicklung [Translational Creativity: Definition—Measurement—Development]. Tübingen: Narr.
    [Google Scholar]
  3. Bennett, Karen
    2013 “English as a Lingua Franca in Academia. Combating epistemicide through translator training.” The Interpreter and Translator Trainer7 (2): 169–193. 10.1080/13556509.2013.10798850
    https://doi.org/10.1080/13556509.2013.10798850 [Google Scholar]
  4. 2014 “The Political and Economic Infrastructure of Academic Practice: The ‘semi-periphery’ as a category for social and linguistic analysis.” InThe Semi-periphery of Academic Writing: Discourses, communities and practices. Edited by K. Bennett , 1–12. London: Palgrave Macmillan. 10.1057/9781137351197_1
    https://doi.org/10.1057/9781137351197_1 [Google Scholar]
  5. 2015 “Towards an Epistemological Monoculture: Mechanisms of epistemicide in European research publication. InEnglish as an Academic and Research Language (English in Europe Vol. 2). Edited by R. Plo Alastrué , and C. Pérez-Llantada , 9–35. Berlin: De Gruyter Mouton.
    [Google Scholar]
  6. Bowker, Lynne , and Jairo Buitrago Ciro Ciro
    2019Machine Translation and Global Research: Towards improved machine translation literacy in the scholarly community. Bingley: Emerald Publishing. 10.1108/9781787567214
    https://doi.org/10.1108/9781787567214 [Google Scholar]
  7. Breuer, Esther O.
    2015First Language versus Foreign Language. Fluency, errors and revision processes in foreign language academic writing. Frankfurt am Main: Peter Lang. 10.3726/978‑3‑653‑04262‑7
    https://doi.org/10.3726/978-3-653-04262-7 [Google Scholar]
  8. Cadwell, Patrick
    2019 “Trust, Distrust and Translation in a Disaster.” Disaster Prevention and Management29 (2): 157–174. 10.1108/DPM‑11‑2018‑0374
    https://doi.org/10.1108/DPM-11-2018-0374 [Google Scholar]
  9. Cadwell, Patrick , Claudia Bollig , and Juliane Ried
    2019 “Management and Training of Linguistic Volunteers: A case study of translation at Cochrane Germany.” InTranslation in Cascading Crises. Edited by F. M. Federici , and S. O’Brien , 152–173. London: Routledge. 10.4324/9780429341052‑8
    https://doi.org/10.4324/9780429341052-8 [Google Scholar]
  10. Cadwell, Patrick , Sharon O’Brien , and Carlos S. C. Teixeira
    2018 “Resistance and Accommodation: Factors for the (non-) adoption of machine translation among professional translators.” Perspectives26 (3): 301–321. 10.1080/0907676X.2017.1337210
    https://doi.org/10.1080/0907676X.2017.1337210 [Google Scholar]
  11. Cadwell, Patrick , Sheila Castilho , Sharon O’Brien , and Linda Mitchell
    2016 “Human Factors in Machine Translation and Post-editing among Institutional Translators.” Translation Spaces5 (2): 222–243. 10.1075/ts.5.2.04cad
    https://doi.org/10.1075/ts.5.2.04cad [Google Scholar]
  12. Chen, Fang , Jianlong Zhou , Yang Wang , Kun Yu , Syed Z. Arshad , Ahmad Khawaji , and Dan Conway
    2016Robust Multimodal Cognitive Load Measurement. Cham: Springer. 10.1007/978‑3‑319‑31700‑7
    https://doi.org/10.1007/978-3-319-31700-7 [Google Scholar]
  13. Ciriello, Livia
    2019 Post-Editing und Kreativität [Post-editing and Creativity]. Master’s Thesis, ZHAW Zurich University of Applied Sciences.
    [Google Scholar]
  14. Coiro, Julie , Michele Knobel , Colin Lankshear , and Donald J. Leu
    2014 “Central Issues in New Literacies and New Literacies Research.” InThe Handbook of Research on New Literacies. Edited by J. Coiro , M. Knobel , C. Lankshear , and D. J. Leu , 1–21. New York; NY: Taylor & Francis. 10.4324/9781410618894
    https://doi.org/10.4324/9781410618894 [Google Scholar]
  15. Cooper, Alan
    2004The Inmates are Running the Asylum: Why hi-tech products drive us crazy and how to restore the sanity. Indianapolis: Sams Publishing.
    [Google Scholar]
  16. Depraetere, Ilse
    2010 “What Counts as Useful Advice in a University Post-Editing Training Context? Report on a case study.” 14th Annual Meeting of the European Association for Machine Translation. AccessedApril 19, 2020. www.mt-archive.info/10/EAMT-2010-Depraetere-2.pdf
    [Google Scholar]
  17. Earley, P. Christopher , and Soon Ang
    2003Cultural Intelligence. Individual interactions across cultures. Stanford, CA: Stanford Business Books. 10.1515/9780804766005
    https://doi.org/10.1515/9780804766005 [Google Scholar]
  18. Ehrensberger-Dow, Maureen , and Sharon O’Brien
    2015 “Ergonomics of the Translation Workplace: Potential for cognitive friction.” Translation Spaces4 (1): 98–118. 10.1075/ts.4.1.05ehr
    https://doi.org/10.1075/ts.4.1.05ehr [Google Scholar]
  19. Elming, Jakob , Laura W. Balling , and Michael Carl
    2014 “Investigating User Behaviour in Post-editing and Translation using the CASMACAT Workbench.” InPost-editing of Machine Translation: Processes and applications. Edited by S. O’Brien , L. W. Balling , M. Carl , M. Simard , and L. Specia , 147–169. Newcastle upon Tyne: Cambridge Scholars.
    [Google Scholar]
  20. EMT
    EMT 2017European Master’s in Translation Competence Framework 2017. Brussels: European Commission.
    [Google Scholar]
  21. Federici, Federico M. , and Christophe Declercq
    eds. 2019Intercultural Crisis Communication. London: Bloomsbury.
    [Google Scholar]
  22. Forcada, Mikel L.
    2017 “Making Sense of Neural Machine Translation.” Translation Spaces6 (2): 291–309. 10.1075/ts.6.2.06for
    https://doi.org/10.1075/ts.6.2.06for [Google Scholar]
  23. Goulet, Marie-Josée , Michel Simard , Carla Parra Escartín , and Sharon O’Brien
    2017 “La traduction automatique comme outil d’aide à la rédaction scientifique en anglais langue seconde: résultats d’une étude exploratoire sur la qualité linguistique. [Machine Translation as an aid for ESL Academic Writing: Results of an exploratory study on linguistic quality].” La revue du GERAS721: 5–28. doi:  10.4000/asp.5045
    https://doi.org/10.4000/asp.5045 [Google Scholar]
  24. Green, Spence , Jeffrey Heer , and Christopher D. Manning
    2013 “The Efficacy of Human Post-editing for Language Translation.” Proceedings of the 2013 ACM SIGCHI Conference on Human Factors in Computing Systems (CHI), 439–448. doi:  10.1145/2470654.2470718
    https://doi.org/10.1145/2470654.2470718 [Google Scholar]
  25. Kappus, Martin , and Maureen Ehrensberger-Dow
    . forthcoming. “The Ergonomics of Translation Tools: Understanding When Less is Actually More.” The Interpreter and Translator Trainer.
    [Google Scholar]
  26. Krings, Hans P.
    2001Repairing Texts: Empirical Investigations of machine translation post-editing processes. Edited by G. S. Koby . Kent, OH: Kent State University Press.
    [Google Scholar]
  27. Langset, Inger Dagrunn , Dan Yngve Jakobsen , and Halvdan Haugsbakken
    2018 “Digital Professional Development: Towards a collaborative learning approach for taking higher education into the digitalized age.” Nordic Journal of Digital Literacy13 (1): 24–39. 10.18261/issn.1891‑943x‑2018‑01‑03
    https://doi.org/10.18261/issn.1891-943x-2018-01-03 [Google Scholar]
  28. Language Industry Survey
    Language Industry Survey 2019Expectations and Concerns of the European Language Industry. AccessedApril 19, 2020. https://euatc.org/wp-content/uploads/2019/11/2019-Language-Industry-Survey-Report.pdf
    [Google Scholar]
  29. Läubli, Samuel , Sheila Castilho , Graham Neubig , Rico Sennrich , Qinlan Shen , and Antonio Toral
    2020 “A Set of Recommendations for Assessing Human–Machine Parity in Language Translation.” Journal of Artificial Intelligence Research671: 653–672. doi:  10.1613/jair.1.11371
    https://doi.org/10.1613/jair.1.11371 [Google Scholar]
  30. Lewis, William
    2010 “Haitian Creole: How to build and ship an MT engine from scratch in 4 days, 17 hours, & 30 minutes.” 14th Annual Meeting of the EAMT. AccessedApril 19, 2020. https://pdfs.semanticscholar.org/9083/5bc87814208e303ebb3e8b58eed03aa4063e.pdf?_ga=2.126917512.445420217.1587735964-1033436181.1587330375
    [Google Scholar]
  31. Lewis, William , Rob Munro , and Stephan Vogel
    2011 “Crisis MT: Developing a Cookbook for MT in Crisis Situations.” Proceedings of the 6th Workshop on Statistical Machine Translation501–511. AccessedApril 19, 2020. https://www.aclweb.org/anthology/W11-21
    [Google Scholar]
  32. Lillis, Theresa , and Mary Jane Curry
    2010Academic Writing in a Global Context: The politics and practices of publishing in English. London: Routledge.
    [Google Scholar]
  33. Martindale, Marianna J. , and Marine Carpuat
    2018 “Fluency over Accuracy: A pilot study in measuring user trust in imperfect MT.” Proceedings of AMTA 201811: 13–25. AccessedApril 19, 2020. aclweb.org/anthology/W18-1803
    [Google Scholar]
  34. Massey, Gary , and Maureen Ehrensberger-Dow
    2017 “Machine Learning—Implications for translator education.” Lebende Sprache62 (2): 300–312. 10.1515/les‑2017‑0021
    https://doi.org/10.1515/les-2017-0021 [Google Scholar]
  35. Mellinger, Christopher D.
    2014 Computer-assisted Translation: An empirical investigation of cognitive effort. Doctoral Dissertation, Kent State University.
    [Google Scholar]
  36. Moorkens, Joss , Antonio Toral , Sheila Castilho , and Andy Way
    2018 “Translators’ Perceptions of Literary Post-editing Using Statistical and Neural Machine Translation.” Translation Spaces7 (2): 240–262. 10.1075/ts.18014.moo
    https://doi.org/10.1075/ts.18014.moo [Google Scholar]
  37. Muñoz Martín, Ricardo
    2016 Of Minds and Men—Computers and translators. Poznań Studies in Contemporary Linguistics52 (2): 351–381. doi:  10.1515/psicl‑2016‑0013
    https://doi.org/10.1515/psicl-2016-0013 [Google Scholar]
  38. Nakamura, Jeanne , and Mihaly Csikszentmihalyi
    2002 “Flow Theory and Research.” InThe Oxford Handbook of Positive Psychology. Edited by C. R. Snyder , and S. J. Lopez , 89–105. Oxford: Oxford University Press.
    [Google Scholar]
  39. Nitzke, Jean , Silvia Hansen-Schirra , and Carmen Canfora
    2019 “Risk Management and Post-editing Competence.” The Journal of Specialised Translation311: 239–259.
    [Google Scholar]
  40. Nurminen, Mary
    2019 “Decision-making, Risk, and Gist Machine Translation in the Work of Patent Professionals.” Proceedings of the 8th Workshop on Patent and Scientific Literature Translation. AccessedApril 19, 2020. https://www.aclweb.org/anthology/W19-7204.pdf
    [Google Scholar]
  41. 2020 “Raw Machine Translation Use by Patent Professionals. A case of distributed cognition.” Translation, Cognition & Behavior3 (1): 100–121. 10.1075/tcb.00036.nur
    https://doi.org/10.1075/tcb.00036.nur [Google Scholar]
  42. O’Brien, Sharon
    2005 “Methodologies for Measuring the Correlations between Post-Editing Effort and Machine Translatability.” Machine Translation191: 37–58. doi:  10.1007/s10590‑005‑2467‑1
    https://doi.org/10.1007/s10590-005-2467-1 [Google Scholar]
  43. 2006 “Pauses as Indicators of Cognitive Effort in Post-editing Machine Translation Output.” Across Languages and Cultures7 (1): 1–21. doi:  10.1556/Acr.7.2006.1.1
    https://doi.org/10.1556/Acr.7.2006.1.1 [Google Scholar]
  44. O’Brien, Sharon , Maureen Ehrensberger-Dow , Marcel Hasler , and Megan Connolly
    2017 “Irritating CAT Tool Features that Matter to Translators.” Hermes Journal of Language and Communication in Business561: 145–162. AccessedApril 19, 2020. https://tidsskrift.dk/her/article/view/97229/146028
    [Google Scholar]
  45. O’Brien, Sharon , Michel Simard , and Marie-Josée Goulet
    2018 “Machine Translation and Self-post-editing for Academic Writing Support: Quality explorations.” InTranslation Quality Assessment: From Principles to Practice. Edited by J. Moorkens , S. Castilho , F. Gaspari , and S. Doherty , 237–262. Cham: Springer. 10.1007/978‑3‑319‑91241‑7_11
    https://doi.org/10.1007/978-3-319-91241-7_11 [Google Scholar]
  46. Paas, Fred , Juhani E. Tuovinen , Huib Tabbers , and Pascal W. M. Van Gerven
    2003 “Cognitive Load Measurement as a Means to Advance Cognitive Load Theory.” Educational Psychologist38 (1): 63–71. doi:  10.1207/S15326985EP3801_8
    https://doi.org/10.1207/S15326985EP3801_8 [Google Scholar]
  47. Rossetti, Alessandra , Sharon O’Brien , and Patrick Cadwell
    2020 “Comprehension and Trust in Crises: Investigating the impact of machine translation and post-editing.” Proceedings of EAMT 2020. https://www.aclweb.org/anthology/2020.eamt-1.2.pdf
    [Google Scholar]
  48. Seel, Norbet M.
    ed. 2012Encyclopedia of the Sciences of Learning. New York: Springer. 10.1007/978‑1‑4419‑1428‑6
    https://doi.org/10.1007/978-1-4419-1428-6 [Google Scholar]
  49. Shopova, Tatiana
    2014 “Digital Literacy of Students and Its Improvement at the University.” Journal on Efficiency and Responsibility in Education and Science7 (2): 26–32. 10.7160/eriesj.2014.070201
    https://doi.org/10.7160/eriesj.2014.070201 [Google Scholar]
  50. Somers, Harold
    1997 “A Practical Approach to Using Machine Translation Software.” The Translator3 (2): 193–212. doi:  10.1080/13556509.1997.10798998
    https://doi.org/10.1080/13556509.1997.10798998 [Google Scholar]
  51. Soricut, Radu , and Abdessamad Echihabi
    2010 “TrustRank: Inducing trust in automatic translations via ranking.” 48th Annual Meeting of the Association for Computational Linguistics: 612–621. AccessedApril 19, 2020. https://www.aclweb.org/anthology/P10-1063.pdf
    [Google Scholar]
  52. Spante, Maria , Sylvana S. Hashemi , Mona Lundin , and Anne Algers
    2018 “Digital Competence and Digital Literacy in Higher Education Research: Systematic review of concept use.” Cogent Education5 (1). doi:  10.1080/2331186X.2018.1519143
    https://doi.org/10.1080/2331186X.2018.1519143 [Google Scholar]
  53. Ståhl, Tore
    2017 “How ICT Savvy are Digital Natives Actually?” Nordic Journal of Digital Literacy12 (3): 89–108. 10.18261/issn.1891‑943x‑2017‑03‑04
    https://doi.org/10.18261/issn.1891-943x-2017-03-04 [Google Scholar]
  54. Sweller, John
    1988 “Cognitive Load during Problem Solving: Effects on learning.” Cognitive Science12 (2): 257–285. 10.1207/s15516709cog1202_4
    https://doi.org/10.1207/s15516709cog1202_4 [Google Scholar]
  55. Toral, Antonio , Sheila Castilho , Ke Hu , and Andy Way
    2018 “Attaining the Unattainable? Reassessing claims of human parity in neural machine translation.” AccessedApril 19, 2020. arXiv:1808.10432. 10.18653/v1/W18‑6312
    https://doi.org/10.18653/v1/W18-6312 [Google Scholar]
  56. van Laar, Esther , Alexander J. A. M. van Deursen , Johannes A. G. M. van Dijk , and Jos de Haan
    2017 “The Relation between 21st-century Skills and Digital Skills: A systematic literature review.” Computers in Human Behavior721: 577–588. 10.1016/j.chb.2017.03.010
    https://doi.org/10.1016/j.chb.2017.03.010 [Google Scholar]
  57. Wahler, Madison Elizabeth
    2018 “A Word is Worth a Thousand Words: Legal implications of relying on machine translation technology.” Stetson Law Review481: 109–139.
    [Google Scholar]
  58. Willey, Ian , and Kimie Tanimoto
    2015 “‘We’re Drifting into Strange Territory Here’: What think-aloud protocols reveal about convenience editing.” Journal of Second Language Writing271: 63–83. doi:  10.1016/j.jslw.2014.09.010
    https://doi.org/10.1016/j.jslw.2014.09.010 [Google Scholar]
  • Article Type: Research Article
Keyword(s): cognitive load; digital literacies; MT literacy; use-case scenarios
This is a required field
Please enter a valid email address
Approval was successful
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error