CorpusCALL Symposium: Professional cooperation for DDL and corpus-informed teaching

Research output: Contribution to conferencePaperpeer-review


Professional cooperation across disciplines has always been at the heart of work in both data-driven learning and corpus-informed teaching. Disciplinary corpora have been compiled with the help of professionals of specific fields (e.g. Crosthwaite & Cheung, 2019; Jablonkai, 2020). Computer scientists and language technologists have worked together with applied linguists to develop tools (e.g. Pérez-Paredes et al., 2019; Frankenberg-Garcia et al., 2019) and online platforms for pedagogical purposes (e.g. SKELL, Lextutor, ColloCaid). Work with corpora have informed teaching languages for various professions, especially in the field of languages for specific and academic purposes (e.g. Chitez & Bercuci, 2019). Finally, corpora and data-driven learning (DDL) are increasingly becoming an essential part of professional development in some professions, for example, in teaching and translation (e.g. Frankenberg-Garcia, 2015). In line with this year’s conference theme of “CALL and professionalization”, our symposium showcases such professional cooperation for DDL and corpus-informed teaching. At the same time, it aims to be a platform to initiate discussion around the skills and competences needed for successful application of DDL and corpora in various professional settings.
The first paper, by Madalina Chitez (West University of Timisoara), examines how bilingual written corpora (native language versus foreign language) can be used in research-informed pedagogical practice to provide disciplinary and professional writing support. The presentation reports the findings from a range of corpus-based contrastive studies based on two large corpora: the ROGER corpus (Corpus of Romanian Academic Genres) of novice writing, and the EXPRES corpus (Corpus of Expert Writing in Romanian and English) of expert writing. Both corpora include disciplinary sub-sets of data, which opens up the possibility of simultaneously contrasting discipline-specific writing and different competence levels.
The second paper, by Pascual Perez-Paredes (Universidad de Murcia and Cambridge Language Sciences), discusses how the collaboration between corpus linguists, language teachers, learners and computer engineers led to a proof of concept that tested the limits and affordances of the use of corpus-informed pedagogies such as DDL in mobile-assisted language learning (MALL) (Pérez-Paredes et al., 2019). Despite the impact of MALL in language learning, there are still very few studies on how DDL and corpora can benefit from the spread of mobile uses for self-access (Zhang & Pérez-Paredes, 2019) and instructed education (Chwo et al., 2018).
The third paper, by Peter Crosthwaite (University of Queensland), describes his experiences conducting teacher professional development workshops in corpus literacy for Australian secondary school subject teachers under COVID-19 conditions. He describes subject teachers’ perceptions of corpus applications following training, and the process of working with subject teachers across a range of secondary school subject areas in order to explore their particular needs, hopes and aims for corpus and data-driven learning opportunities. He outlines three ongoing projects arising from these workshops, including a suite of corpus activities and training for science teachers working with Year 9-10 students and developing training and support for teachers working with English as an additional language across a range of mainstream subject courses.
The fourth and last paper, by Ana Frankenberg-Garcia (University of Surrey), reports on her experience of delivering continuing professional development (CPD) workshops on the use of corpora in everyday translation practice for professional organizations such as the Institute of Translation and Interpreting, the EU Commission DG-Translation, and the Chartered Institute of Linguists. Many of today’s practicing translators have heard of corpora, and some may have even attended introductory lectures in corpus linguistics. However, few have had actual hands-on training on how to use corpora to enhance the quality of translations, extract terminology and familiarize themselves with specialized language varieties.

Chitez, M. & Bercuci, F. (2019). Data-driven learning in ESP university settings in Romania: multiple corpus consultation approaches for academic writing support. In F. Meunier, J. Van de Vyver, L. Bradley & S. Thouësny (Eds.). CALL and complexity, (pp. 75- 81). Research
Chwo, G. S. M., Marek, M. W., & Wu, W. C. V. (2018). Meta-analysis of MALL research and design. System, 74, 62-72.
Crosthwaite, P. & Cheung, L. (2019). Learning the language of dentistry Disciplinary corpora in the teaching of English for Specific Academic Purposes. John Benjamins Publishing.
Frankenberg-Garcia, A. (2015). Training Translators to Use Corpora Hands-on: challenges and reactions by a group of 13 students at a UK university. Corpora, 10(2), 351-380.
Frankenberg-Garcia, A., Lew, R., Roberts, J., Rees, G. and Sharma, N. (2019). Developing a writing assistant to help EAP writers with collocations in real time, ReCALL 32(2), 23-39.
Jablonkai, R. R. (2020). Leveraging professional wordlists for productive vocabulary knowledge. ESP Today 8(1), 2-24.
Pérez-Paredes, P., Ordonana Guillam, C., Van de Vyver, J., Meurice, A., Aguado Jimenez, P., Conole, G., & Sanchez Hernandez, P. (2019). Mobile Data-driven language learning: affordances and learners’ perception. System, 84,145-159.
Zhang, D. & Pérez-Paredes, P. (2019) Chinese postgraduate EFL learners’ self-directed use of mobile English learning resources. Computer Assisted Language Learning
Original languageEnglish
Publication statusAcceptance date - Aug 2021
EventEuroCALL 2021: CALL & Professionalisation - virtual, Paris, France
Duration: 26 Aug 202127 Aug 2021


ConferenceEuroCALL 2021
Internet address


Dive into the research topics of 'CorpusCALL Symposium: Professional cooperation for DDL and corpus-informed teaching'. Together they form a unique fingerprint.

Cite this