D ata L it MT – Teaching Data Literacy in the Context of Machine Translation Literacy (2023)

Abstract: This paper presents the DataLitMT project conducted at TH Koln – University of Applied Sciences. The project develops learning resources for teaching data literacy in its translation-specific form of professional machine translation (MT) literacy to students of translation and specialised communication programmes at BA and MA levels. We discuss the need for data literacy teaching in a translation/specialised communication context, present the three theoretical pillars of the project (consisting of a Professional MT Literacy Framework, an MT-specific data literacy framework and a competence matrix derived from these frameworks) and give an overview of the learning resources developed as part of the project.

## introduction in recent years, the professional translation industry has seen accelerating processes of digitalisation -in the form of powerful new artificial intelligence algorithms in the field of natural language processing (nlp) and beyond (most recently, the transformer neural network architecture by @xcite -and datafication -through accumulating large volumes of translation data for training translation-specific nlp applications such as neural machine translation (nmt) systems. this has led to a considerable increase in translation automation, mostly through the integration of nmt systems in translation production workflows (e.g., @xcite . accordingly, an adequate degree of machine translation literacy @xcite is becoming more and more relevant for professional translators. in translation studies, the concept of mt literacy has been applied both to professional translators working in mt-assisted translation production networks, and to layperson audiences @xcite , who can use powerful mt technology as cloud-based "everyware" @xcite in their daily lives and should thus have a basic understanding of this technology. in order to delineate layperson mt literacy from mt literacy geared towards professional translators, @xcite define professional mt literacy as "the full range of mt-related competences professional translators (and other language professionals) may require in order to participate successfully in the various phases of the mtassisted professional translation process". the concept of professional mt literacy was then further expanded in a professional mt literacy framework, which we discuss in more detail in section 3.1. parallel to the increasing relevance of mt literacy for professional and layperson audiences, adequate data literacy is also becoming more and more important, both at the overall level of modern datafied societies and at the level of specific professional fields (such as translation), where management and production processes have also become increasingly datafied in recent years @xcite . against this background, data literacy is seen as a key prerequisite for enabling people to "navigate the complexity of modern data ecosystems" (ibid.). @xcite define data literacy in a rather general way as "the ability to collect, manage, evaluate, and apply data, in a critical manner". other authors attempt more context-bound conceptualisations of data literacy, situating it, for example, within the process of knowledge creation @xcite or within the overall data lifecycle @xcite . a common thread running through these different approaches is that they not only highlight the technical dimension of this concept but also stress that adequate data literacy involves critical awareness of the impact of using data in various application contexts. there is an immediate link between (professional) mt literacy and data literacy, since modern corpus-based mt systems have to be trained on large volumes of high-quality translation data in order to produce high-quality translations @xcite . from this perspective, data literacy can be seen as an important building block of (professional) mt literacy. we expand upon the interface between mt literacy and data literacy in section 3.3. ## datalit mt the datalit mt project is based at the institute of translation and multilingual communication at th köln -university of applied sciences, cologne, germany. datalit mt starts from the following premise: although data literacy education is becoming increasingly relevant for students of translation and specialised communication programmes due to the increasing datafication of the respective professional fields and the growing societal relevance of data literacy as discussed above, there is less of a 'natural fit' between data literacy and these study programmes -which have traditionally focused more on linguistic, communicative and (inter)cultural aspects -than, for example, between data literacy and more technology-focused programmes such as computer science, data science or computational linguistics. for data literacy education in a translation/specialised communication context to be feasible, we must therefore first establish suitable points of contact between data literacy and topics which are more central to translation and specialised communication. datalit mt assumes that machine translation is well-suited to serve as a conceptual bridge between data literacy on the one hand and translation and specialised communication on the other. in the preparatory stage of datalit mt , we conducted a small survey among the students of the ba and ma programmes at the institute of translation and multilingual communication at th köln. as part of the survey, we asked students for their free associations with the term "data literacy". figure 1 illustrates the answers given (@xmath0. as can be seen, the most common associations are "handling data" (@xmath1, "analysing data" (@xmath2, and "no idea" (@xmath3, "processing data" (@xmath4. we interpret these results as follows. despite its high societal and professional relevance as discussed in section 1, the term data literacy does not seem to be universally known to students ("no idea"=5). several students already link data literacy to machine translation, which highlights the interface between the two concepts to be exploited by datalit mt . finally and perhaps not surprisingly, most of the students' associations are related to 'hands-on' steps of working with data (handling/analysing/processing data). more abstract and higher-level aspects of data literacy, such as critical thinking and data ethics, as well as strategic aspects, such as data requirement analyses or data-driven decision making (see the discussion of our data literacy framework in section 3.2), seem less immediately obvious to students. although based on a small and non-randomised sample, these results can be taken to indicate both the general need of comprehensive data literacy education and the feasibility of our basic didactic idea of teaching data literacy in an application context which will already be familiar to students of translation/specialised communication programmes. against this backdrop, the datalit mt project develops learning resources for teaching data literacy in its translation-specific form of professional mt literacy aimed at translation and specialised communication programmes at ba and ma levels. the learning resources are made publicly available on the datalit mt website foot_0 and github repository foot_1 . the project also comprises a youtube channel with tutorial videos for individual learning resources foot_2 . ## theoretical pillars of datalit mt in the preparatory stage of datalit mt , we developed a professional mt literacy framework and an mtspecific data literacy framework (datalit mt framework) @xcite in order to provide internal structure to the two frames of reference relevant to the project and to identify points of contact between them. based on the interface between the two concepts, we then developed a competence matrix (datalit mt competence matrix) (krüger and hackenbuchner, forthcoming) comprising mt-specific competence descriptors for the individual (sub)dimensions of the datalit mt framework. ## datalit mt learning resources in this section, we discuss the open educational learning resources that we developed based on the competence matrix illustrated in the previous section. the resources are not set up as comprehensive course syllabi, but are intended to complement translation technology/nlp courses or courses with other foci (e.g. on ethical aspects of the professional translation industry) in translation and/or specialised communication programmes. the resources can be used as extensive lecture materials in the classroom (or for self-study purposes) to theoretically explain and practically exemplify various aspects of mt-specific data literacy. for example, at th köln, several of the datalit mt learning resources will complement introductory courses on translation technology in our ba in multilingual communication programme and advanced translation technology and mt-specific courses in our ma in specialised translation and ma in terminology and translation technology programmes. all learning resources are written in english to expand the international reach of this project. they are published under a creative commons by-sa-4.0 license and made publicly available on the datalit mt website foot_4 . section 4.1 provides an overview of the full range of learning resources developed for datalit mt and section 4.2 zooms in on one particular learning resource concerned with mt-specific data collection/production. ## conclusion & outlook this paper presented the datalit mt project, which develops learning resources for teaching data literacy in its translation-specific form of professional mt literacy to students of translation and specialised communication programmes at ba and ma levels. we hope that these resources help students develop an adequate degree of data literacy cum mt literacy both for their later professional careers in the translation/specialised communication sector or beyond and for their role as citizens in modern digitalised and datafied societies. since the project was completed only recently (february 2023), we do not yet have any data on the didactic effectiveness of the learning resources in actual teaching scenarios. we intend to investigate this in a followup study at th köln. in the future, we also aim to expand our work on transversal digital literacies relevant to the fields of translation/specialised communication and at societal level to include artificial intelligence literacy, which long and magerko (2020) define as "a set of competencies that enables individuals to critically evaluate ai technologies; communicate and collaborate effectively with ai; and use ai as a tool online, at home, and in the workplace". professional translation has been a forerunner in ai-based automation in recent years, mostly due to the implementation of nmt in production systems since 2016. more recently, powerful large language models based on vaswani et al.'s transformer architecture have emerged, perhaps most notably in the form of chatgpt foot_12 . the powerful generative capabilities of chatgpt and related models have extended ai-based automation far beyond its previous scope of application, making an adequate degree of ai literacy of the citizens whose societies are about to be transformed by ai a pressing matter. since modern ai technologies such as nmt or the gpt language models rely on large volumes of high-quality training data, there is an immediate link between data literacy, mt literacy and ai literacy. it can therefore be assumed that a solid data literacy/mt literacy education as discussed in this paper may act as a stepping stone for a more extensive ai literacy education.