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Machine translation – how teachers can deal with online translation tools in language studies assessments

Online machine translation tools offer many advantages in everyday communication but what concerns do they raise among language teachers when they’re used in assessments? This article examines the issues involved.

This content is associated with The Open University's Language courses and qualifications.



‘So how can we create assessment tasks for language learners in times of digital machine translation tools…’ 

Karina von Lindeiner-Stráský is leading a research team at The Open University, exploring the use of machine translation tools in language learning, teaching, and assessment. The team's research has revealed the key issues language tutors at The Open University, where most teaching is carried out long distance and online, are concerned about:

  • Depending on the languages it has become nearly impossible for teachers to identify texts submitted for assessment that students have produced with the help of online translation tools. And if they do, they usually cannot prove it.
  • Teachers consider the use of translation tools by students unfair on those learners who make the effort to submit their own work.
  • Students who use online translation tools miss out on the actual learning potential that is an important part of carefully crafted assessments.

A graphic of a globe with the word translate in many different languages over the different countries


So how can we create assessment tasks for language learners in times of digital machine translation tools? It seems that assessment strategies that focus on students producing linguistically accurate texts in the target language are now inadequate.

Instead, we must employ new strategies to adapt language exams to the new technological realities of learning and studying. Three approaches, or a mixture of them, may help us to solve the dilemma:

  • It is essential there are clear definitions of what constitutes good and acceptable academic practice in the respective assessment context. Rules for the uses of translation tools and citations, and established formal policies regarding student use of machine translation in assessment, give both students and teachers/assessors confidence and security. These rules and regulations have to be clearly communicated.
  • Exam conditions and marking criteria can be adapted to limit the influence online translation tools have on the results. In essence, this means a shift from the assessment criterion ‘accuracy’ to ‘reflection’ and a general diversification of assessment criteria. Another, more ‘googleproof’ way to examine is, for example, a portfolio-style assessment with a variety of tasks, or interactive assessment. For instance, two students or a student and a tutor can interact in dialogue, or students respond spontaneously to prompts.
  • New assessment activities can be developed that take into account or actively build on the potential of online machine translation tools as a learning and assessment tools. Some ideas include:  

  1. Students demonstrate their understanding of the language taught by actively using it in their own work. For example, they formulate their own sentences, using specific language taught in the course. This enforces the application of taught structures through prescriptive assessment design.
  2. Students reflect on and explain texts in different styles, registers or different text types, perhaps produced with the help of machine tools. So they demonstrate appropriate linguistic capability beyond the production of target language texts.
  3. Students identify and explain mistakes in a text, demonstrating their knowledge of accuracy and language structures.
  4. Students show their ability to comprehensively handle various linguistic structures and demonstrate their cultural awareness. For example they analyse and explain two different media such as videos and images, or use language creatively.

These and similar assessment activities support and enforce the shift that can be observed in language teaching in times of online translation tools: the emphasis of language learning shifts from the acquisition of linguistic knowledge and the emphasis on accuracy to imparting cultural awareness, use of register, and idiomatic language.


References, sources and links

Ducar, C., and Schocket, D. H. (2018). Machine translation and the L2 classroom: Pedagogical solutions for making peace with Google translate. Foreign Language Annals, 51(4), 779-795. 

von Lindeiner-Stráský, K. (2022).  unpublished project report ‘Web-based Machine Translation in Language Learning, Teaching, and Assessment’, Praxis-Project, The Open University 2020-2022.



 

 


 






 

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