Innovation in Language Learning

Due to the importance of Languages for Specific Purposes (LSP) (Kastberg, 2018) in our globalised society, Higher Education institutions have to prepare students for the acquisition of domain-specific knowledge in as many areas as possible. The exploration of specialised corpora assumes a key role in that respect, as it provides access to domain-specific texts that allow the study and description of linguistic patterns and phenomena of a certain field area. The use of comparable corpora as an important auxiliary for the analysis and description of LSP provides the students with valuable tools for data-driven learning (DDL) (Gilquin & Granger, 2010). Working with domain-specific texts demands, apart from the identification of specific linguistic patterns, the ability to differentiate among a variety of communicative situations. These communicative situations require competence in the application of specific registers that range between specific domain language and popular discourse, the latter being the product of a simplification process involving a series of different strategies. The identification and analysis of such strategies contributes to the students' awareness raising and critical reflection. In this study, we aim at familiarising students with science popularisation strategies in the field of environment and climate change policies. In this DDL approach, students make use of ChatGPT for the simplification of LSP and identify science popularisation strategies in German and Portuguese. Based on the results, we aim at reflecting on the possibilities and limitations of using OpenAI in a Higher Education setting.