Employment prospects for graduates in language-related disciplines (linguistics, foreign languages, language pedagogy, translation and interpreting) are still mainly focused on teaching positions or positions as translators. This stands in stark contrast with their potential employability given the omnipresence of language and communication in society and the number of companies that make language their main business. 

The central goal of the UPSKILLS project is to identify and tackle these skills gaps and mismatches through the development of a new curriculum component and supporting materials to be embedded in existing linguistics and language-related programmes. To this end, we aim at introducing an integrated research-oriented perspective into language-related programmes, with a focus on the BA level, that is expected to enhance students’ employability by providing them with the skills needed to compete for a wider range of positions in the labour market. Our consortium works together with companies to cover real-world tasks and incorporate scenarios of technology use in the designed learning material. At the same time, we seek to integrate existing research into teaching by promoting inquiry-based learning, and by organising training of the trainers events. The dissemination of our unified curriculum component and the research leading to its compilation is planned to take place through dedicated multiplier events aimed at participants from 20+ countries.


September 2020 – August 2023

The development of our new study component is articulated through four intellectual outputs:
1. Needs analysis

Our in-depth needs analysis seeks to develop a detailed professional profile for graduates of linguistics and language-related courses, with the associated learning objectives (knowledge, skills and competences), typical tasks and responsibilities. Preliminary findings already point to the necessity for language and linguistics students to develop a new skill set and a new mind frame to meet the societal and professional challenges lying ahead.

Against this backdrop, our needs analysis is divided into two parts. The first one comprises a series of surveys aiming to map competences and skills currently covered in BA and MA programmes in languages and linguistics, as well as market demands targeting graduates in these fields. Activities carried out within this part consist, on the one hand, of surveys of existing languages/linguistics curricula offered by European higher education institutions, and a systematic review of the literature on the integration of digital and analytical skills in humanities courses. On the other hand, it includes a corpus-based analysis of job posts on LinkedIn and similar online employment-oriented platforms, and the administration of targeted surveys to representatives of companies that hire linguists/language specialists in the partner countries. In the second part, follow-up focus group interviews with selected stakeholders aim at further refining and clarifying the insights obtained, particularly as concerns future-proofing higher and continuing education in the domain of language/linguistics.

Our needs analysis targets three groups of beneficiaries. For one, language and linguistics students who look to expand on or update their skillset will benefit from a clearer understanding of the expectations of the world of work, which translates into knowing what they should learn, but also knowing how to apply existing knowledge, skills and competences to novel work requirements. Then, employers from digital and data intensive sectors, who currently fail to identify language and linguistics graduates as a target talent pool for their business, will benefit from the co-construction and dissemination of a specific job profile with associated competences, skills and knowledge. Finally, the perception of academic interlocutors (lecturers, degree coordinators, heads of schools), who often show resistance toward scientific content in a humanities curriculum, is bound to be affected by solidly collected data about the employment potential for language and linguistics students in digital sectors, and by international best practices in this field. 

2. Best practices and guidelines for research-based teaching

While the benefits of research-based teaching are increasingly being recognised, its practical aspects still need to be elaborated.For this intellectual output, the UPSKILLS partners are documenting the steps needed for incorporating ongoing research into teaching, focusing not only on academic and industry-based research, but also on the integration of research infrastructures into teaching. In this regard, our guidelines seek to address a wide array of issues ranging from didactic (how to define students’ assignments in order to maximise acquisition of new skills while avoiding non-educative labour) to practical (how to use appropriate research infrastructure).

More specifically, this intellectual output includes syllabi and descriptions of revamped modules in language-related subjects, which are designed to combine research questions and data analysis from actual research (including data collection) with the dedicated learning objectives and content developed under intellectual output 3. Each module is  organised around a research problem, where the students will acquire and actively apply analytic skills on actual data; depending then on the nature of the problem, certain modules will involve students’ engagement with the acquisition of data (corpus-building, corpus research, experimentation), while others will target a particular conceptual domain (e.g. morphological paradigms).

This intellectual output seeks to assist teaching staff in offering more meaningful assignments, which will evolve together with the topics and standards of ongoing research, as well as students in gaining experience and skills more in tune with the contemporary work requirements. In this respect, students will be able to experience the authentic collaborative research process – from the data-gathering to the analysis phase – before graduating and taking up an actual job.

3. Curriculum design and development

This intellectual output involves the collection and creation of learning content as well as compilation of materials to be presented to students in the form of research project tasks. The selection for this learning content is based on previous experiences by the project partners and some initial findings of our needs analysis, and can be roughly grouped in three blocks, according to the type of transferable skills they focus on:

1) Research skills: Introduction to scientific research; Analytical thinking and problem solving; Project management

2) Data acquisition skills: Introduction to programming; Text and speech processing (including corpus creation and use, recording and transcription of spoken data); Collecting data from human subjects (covering linguistic fieldwork, experiments, collection of judgements)

3) Data handling skills: Introduction to machine learning (focused on language data); Data standards and repositories (using existing language resources and tools, developing new ones with FAIR principles and GDPR, data management standards, licencing and depositing new resources and tools); Language data science (including inferential statistics)

Additional cross-cutting components, present throughout the listed units, are linguistic theory (with a focus on intriguing questions and existing explanations) and research and data management software (used for tracking the process of research and data flow).

All topics are being handled in both a theoretical and applied fashion, with the inclusion of lectures and reading material on the one hand, and practical and group work on the other. In order to avoid material fragmentation with limited usage, we integrate already existing open educational resources from other projects, by the current partners and beyond, while at the same time creating other parts of the learning content ab ovo. On the practical side, alongside smaller tasks, the students will also be given an opportunity to participate in virtual showcases based on the theoretical material provided, where they would formulate examples of good research design and compare different approaches to similar research questions. 

Against this background, the central target groups of this intellectual output are students in language-related fields and lecturers who would incorporate the developed content, and/or add their own, into their teaching.

4. Enriching the curriculum through educational games

Although educational games have been used in language learning, their use for the development of transferable skills as part of the curriculum in linguistics and language-related disciplines is still comparatively rare. This intellectual output is dedicated to creating guidelines for the integration of educational games in the relevant teaching through the introduction of novel content from different disciplines. More specifically, it will comprise instructions for lecturers on how to use games in their teaching as well as manuals on how to populate existing games with content they have created.

Educational games are a relatively novel teaching mode that provides students with the possibility to engage in situated experiences, thus helping them overcome barriers related to physical, geographical and temporal boundaries. They also allow for interactive learning, which is attractive for many students, since it adds an element of engagement and motivates them to advance their knowledge and their skills by mastering the content while exploiting elements of fun. For lecturers, educational games provide the possibility to train students and give them materials in a modular fashion, also without having to be in the same room with them at a given time. In addition, they can be used to keep a log of decisions taken by students, which would provide lecturers with tangible data regarding their students’ preferences and aptitudes, helping them better tailor their materials to enhance both student satisfaction and impact on learning.