This paper presents the results of a case study investigating the translation of German phraseological units into Italian using four AI-powered translation tools. The aim is to systematically analyse and compare the translations produced by these tools. This study can be used as a model for analysing other linguistic phenomena and contributes to the evaluation of automated translation systems in the field of phraseology. The article begins with an introduction to AI-powered translation programmes and their function as text transformers (Section 1), followed by a description of the methodology (Section 2). Section 3 focuses on data analysis, examining the various translation outputs offered by the tools, especially translation alternatives and supplementary information (e.g. comments on the translation), depending on whether the input phraseological units are provided with or without context. Section 4 offers a summary and conclusion.
This article explores how university GFL learners can meaningfully utilise artificial intelligence (AI) for translation, focusing on literary translation. The paper presents the results of a small-scale study conducted in parallel at two Italian universities, in which intermediate-level students (B1+ to B2) translated two literary texts using the AI-powered translation tool DeepL. The study considers the potential implications for university teaching.
This article examines digital and hybrid teaching formats in higher education, focusing on academic seminars in German as a foreign language (DaF – Deutsch als Fremdsprache). It discusses how the shift towards virtual communication, accelerated by the pandemic, has reshaped interactional dynamics and necessi-tated new strategies for managing distance and complexity in knowledge trans-mission. Employing a media-theoretical and conversation-analytical framework, and drawing on empirical data, the study compares digital and hybrid lectures, identifying their distinctive communicative features. !e article also considers the potential future role of artificial intelligence in hybrid university teaching.
This article examines possible future directions for school and university writing in the age of AI. It outlines three ideal-typical scenarios: Delegation (outsourcing human writing to AI), Konservation (preserving human writing in contrast to AI), and Transformation (reshaping human writing in response to AI). None of these scenarios is likely to be fully realised in the coming years, yet the analysis points to Transformation as the only sustainable option.
This article presents the preliminary findings of a study examining the use of the ChatGPT-4o-mini version of OpenAI's large language model (LLM) for revising student summaries. It should be noted that the statements and conclusions in this study refer exclusively to this LLM in this specific iteration. This study is based on the principles of sociological role theory and subsequent critiques of the theory. To this end, we propose a theoretical framework to delineate the unique requirements of written dialogue between students and the LLM behind ChatGPT. This framework is designed to facilitate coordination between human and artificial intelligence in the text writing process. Following the theoretical considerations, the expectations and assumptions regarding the potential of ChatGPT are examined, as these influence the linguistic and communicative behaviour of LLM users.
