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Das P8-Projekt «Digital Literacy im Hochschulkontext» hat gezeigt, dass maschinelle Übersetzung sowohl von Studierenden als auch von Dozierenden an Schweizer Hochschulen regelmässig für das Verfassen und die Übersetzung aller Arten von Dokumenten verwendet wird. Allerdings geschieht diese Verwendung bisher fast immer ohne explizite Instruktion und Sensibilisierung für den Umgang mit digitalen Tools, die auf künstlicher Intelligenz beruhen. In dieser Präsentation geben wir einen kurzen Überblick darüber, was MT-Literacy, also der verantwortungsvolle und kompetente Umgang mit maschineller Übersetzung, im Hochschulkontext bedeutet und beinhaltet. Anhand dieses Beispiels zeigen wir auf, dass Digital Literacy verschiedene Komponenten beinhaltet, von Wissen über die Tools, ihre Potentiale und Risiken bis hin zu Soft Skills, wie eine selbstbewusste Haltung und realistische Einschätzung der eigenen Fähigkeiten. In diesem Zusammenhang beleuchten wir auch die immer häufiger zum Einsatz kommende KI-basierte Textgenerierung und welche Möglichkeiten diese für die Lehre eröffnet. Anhand des Einsatzes von KI-basierten Tools für das Verfassen von Texten zeigen wir Aspekte auf, die für den Umgang mit künstlicher Intelligenz in der Lehre und das Zusammenspiel von Mensch und Maschine wichtig sind und für verschiedene Arten von Lehrszenarien relevant sein können.

The advent of neural machine translation in 2016 catapulted machine translation (MT) into a world that was already digitalizing at an accelerated pace. The last decade has also witnessed the digitalization of most well-established dictionaries (Merriam-Webster, Robert, Pons, Duden, etc.), including free online access and the emergence of bilingual concordancers (Linguee). As a result, language learners and translation students can use numerous online resources with a simple click. However, the process behind many online dictionaries (OD) is still human lexicographic work, while MT provides output based on natural language processing, i.e. artificial intelligence (AI), without human validation. A survey carried out among Swiss universities in 2021 shows that, in the context of higher education, machine translation tends to be used as a surrogate for online dictionaries. This chimes with observations by Briggs (2018) and O'Neill (2019), who noted an almost identical use of MT and OD amongst students. In the present survey, a large proportion of the respondents indicate that they use online MT systems primarily to look up words or to find synonyms. This conflation of MT and OD works both ways: respondents cited bilingual dictionaries when asked what MT systems they use. Further, the physical distinction between the two types of linguistic resources is also fading, since many online MT tools now include dictionary functions and vice versa. In this situation, the authority of human lexicographers seems to be tacitly challenged by AI and demonstrates the need to elucidate how human knowledge and AI should interact for building, maintaining and using linguistic resources. This communication will present the data consolidating this affirmation and will discuss practical consequences and implications, especially with respect to training needs in the area of MT literacy (Bowker 2020) and the informed use of digital literacy tools.

Since the beginning of the 21st century, translation methods have made a comeback in the language classroom, as is acknowledged in the new CEFR Companion Volume with New Descriptors (2018, see chapter called “Mediation”). Recent research has emphasised the cognitive, psychological, linguistic, cultural, pragmatic and educational gains brought by translation (De Carlo 2012). This trend parallels the emergence of new free translation tools on the Internet (systems like DeepL or Google Translate), which have simplified the availability and quality of machine translation for both teachers and students. Whereas students tend to use these tools quite extensively even if they don’t trust them blindly (Briggs 2018), teachers fear them because they are thought to induce students’ laziness (Van Praag and Sanchez 2015).Nevertheless,there have been some attemptsto include translation technology as a tool for CALL (Yamada 2020). Our four-year swissuniversities project aims to better understand the impact of neural machine translation (NMT) on students and teachers’ habits and to collect indicators of their attitudes and perceptions. The paper will present the results of a survey we conducted in four Swiss universities andwhichwassent to students and staff to enquire abouttheir use of NMT and their attitudestowards it. The panorama of practices and perceptions obtained through the survey will be analysed to shape pertinent instruction modules on NMT literacy (Bowker and Buitrago Ciro 2019) aimed at language teachers and students. With these interventions, we wish to contribute to the professionalisation of pedagogical practices around NMT and encourage awareness of intellectual and ethical implications of plagiarism through translation. Furthermore, we aim to give language teachers a good grasp of NMT-related issues so that they may move from their negative attitudes towards a more balanced view of NMT in language learning and teaching.

Switzerland has four national languages and English is frequently used as a lingua franca. It is therefore paramount to foster inclusion and national unity while maintaining language diversity. In the context of Swiss universities in particular, the language question is of daily concern, as researchers participate in cross-regional and pan-European networks. Recent advances in machine translation have led to frequent and generalized use, which could help foster language diversity. However, users are rarely aware of the pitfalls of such technologies and therefore tend to blindly trust them, sometimes leading to misunderstandings with far-reaching consequences. Students in language classes are no exception: While they already know and employ free neural machine translation solutions (e.g. DeepL, Google Translate), they lack both information about how these technologies work and clarity about how reliable their output is. This leads to uncritical use. Conversely, although these tools are familiar to teachers, they rarely use them in language teaching, as they are sometimes reluctant to adopt new technologies which they regard as disruptive or even as a threat to language teaching. Also, many teachers feel powerless when facing what they see as a major problem, especially when evaluating student texts. However, translation technology can also be considered as a tool for CALL (Yamada 2020). The project we present started in January 2021 and sets out to develop machine translation literacy (Bowker & Buitrago 2019) among Swiss university language teachers and students, beginning by better understanding the reality of language teaching and learning in higher education in the era of machine translation. For the first time, Swiss university students and staff will be surveyed about their use of machine translation. More specifically, we seek to understand in what context, for what purposes, with what degree of successive revision and with what ethical considerations machine translation is used. The proposed communication will present the results of this survey conducted in four Swiss universities with over 3500 participants and the initial conclusions that can be drawn from it regarding the possibility of harnessing machine translation literacy for foreign language learning and teaching. The panorama of practices obtained through the survey will enable us to determine concrete pedagogical objectives and develop targeted interventions on machine translation literacy both for teachers and students. These interventions will contribute to professionalizing pedagogical practices around machine translation, strengthen the linguistic independence of future Swiss professionals and encourage awareness of the intellectual and ethical implications of plagiarism through translation. At a societal level, they should also foster linguistic diversity by helping to develop greater confidence among Swiss citizens to read and produce texts in a national language other than their first language.