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Using DeepL translator in learning English as an applied foreign language – An empirical pilot study

Petra Poláková, Blanka Klímová

2023Heliyon43 citationsDOIOpen Access PDF

Abstract

With the advent of new emerging technologies, machine translation, especially natural machine translation (NMT) and its tools, is being increasingly applied in second language (L2) acquisition. The aim of this study is to investigate the usefulness of machine translation, specifically DeepL Translator, in the second language acquisition process, since it has a great potential to transform foreign language education. The present empirical pilot study describes an experiment dealing with the use of neural machine translation in the process of formal writing (i.e., writing a summary) in a foreign language. Altogether 16 university students learning English as an applied foreign language with C1 level of English proficiency participated in the experiment. The results show differences between pre-test and post-test, and a significant improvement in students' language skills due to the use of DeepL Translator. The questionnaire survey, among other things, reveals positive perceptions of this tool and awareness of improved language skills by the research participants. The findings indicate that purposefully guided working with a NMT tool can contribute to the perceived usefulness of its use in learning English as an applied foreign language.

Topics & Concepts

Machine translationComputer scienceForeign languageTest (biology)Language assessmentEmpirical researchProcess (computing)Language acquisitionEnglish as a foreign languageFirst languageEnglish languageLanguage industryNatural language processingArtificial intelligencePerceptionNatural languagePsychologyComprehension approachMathematics educationLinguisticsBiologyNeurosciencePhilosophyEpistemologyPaleontologyOperating systemNatural Language Processing TechniquesText Readability and SimplificationSecond Language Acquisition and Learning