The rapid development of Artificial Intelligence (AI) has profoundly transformed translation practices and poses new challenges for higher education. This article presents a multi-stage teaching project designed for MA students that critically explores the potentials and limitations of AI-based translation tools. Through the comparative analysis of literary and contemporary texts—most notably Franz Kafka’s short prose piece “Gib’s auf ”—students examine outputs from tools such as DeepL, Google Translate, ChatGPT, and Matecat. The project combines text analysis, comparison of machine translations, post-editing, and collaborative translation workshops, including direct interaction with a contemporary author. Results show that while AI tools provide efficient and often accurate support, they remain limited in conveying stylistic nuance, pragmatics, and cultural meaning. The study demonstrates that translation quality depends on human interpretation, creativity, and responsibility, highlighting AI as a didactic catalyst rather than a substitute for professional translational competence.

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Moderner Übersetzungsunterricht unter Nutzung digitaler Technologien

  • Anja Lange,
  • Iryna Gaman

摘要

The rapid development of Artificial Intelligence (AI) has profoundly transformed translation practices and poses new challenges for higher education. This article presents a multi-stage teaching project designed for MA students that critically explores the potentials and limitations of AI-based translation tools. Through the comparative analysis of literary and contemporary texts—most notably Franz Kafka’s short prose piece “Gib’s auf ”—students examine outputs from tools such as DeepL, Google Translate, ChatGPT, and Matecat. The project combines text analysis, comparison of machine translations, post-editing, and collaborative translation workshops, including direct interaction with a contemporary author. Results show that while AI tools provide efficient and often accurate support, they remain limited in conveying stylistic nuance, pragmatics, and cultural meaning. The study demonstrates that translation quality depends on human interpretation, creativity, and responsibility, highlighting AI as a didactic catalyst rather than a substitute for professional translational competence.