Data-Driven Learning for Writing Skills Development

Authors

Mirjana Borucinsky
Faculty of Maritime Studies, University of Rijeka, Croatia
https://orcid.org/0000-0002-1132-9720 (unauthenticated)
Jana Kegalj
Faculty of Maritime Studies, University of Rijeka, Croatia
https://orcid.org/0000-0001-6134-709X (unauthenticated)

Synopsis

Exposing students to corpus-informed research is a typical example of data-driven learning. This paper reports on the ways that corpora (i.e., text collections), corpus tools (i.e., software packages), and corpus methods (i.e., techniques for analysing corpus data) can be used to develop students’ writing skills, while enabling them to improve their digital competencies, which is in line with current trends in education. The authors present and discuss the ways that corpus-derived materials can be developed for teaching writing skills with the goal of engaging students during their learning process and enabling them to conduct their own linguistic research. The data-driven learning (DDL) method based on corpus search was implemented in a specialized course aimed for doctoral students at the University of Rijeka Faculty of Maritime Studies. The course, implemented within the UNIRI CLASS A2 Digital Citizenship—Innovations in Learning and Teaching in 2022 project line, aimed to use the corpus-based data-driven learning method to develop students’ academic writing skills. This was intended to make students more independent and autonomous in their learning, to enhance their digital skills, and to stimulate them to be more involved in their own learning.

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Published

January 9, 2025

How to Cite

Borucinsky, M. ., & Kegalj, J. . (2025). Data-Driven Learning for Writing Skills Development. In L. . Grčić & M. . Brkić Bakarić (Eds.), Corpora in Language Learning, Translation and Research: Proceedings of the International Conference Corpora in Language Learning, Translation and Research held at the University of Zadar (August 23–24, 2023) (pp. 34-48). Morepress Books. https://doi.org/10.15291/9789533315355.04