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Abstract

This study aims to describe and compare DeepL and ChatGPT translations of the Brothers Grimm fairy tale Rotkäppchen from German into Indonesian based on Nida and Taber’s principle of dynamic equivalence. The study employs a qualitative descriptive approach with a comparative design. The data sources consist of the German text of Rotkäppchen from Kinder- und Hausmärchen (1857) and its translations produced by DeepL and ChatGPT. The analysis focuses on lexical, grammatical, semantic, pragmatic, and stylistic aspects while considering the preservation of meaning, context, target-language naturalness, and communicative effect. The findings indicate that the two tools exhibit different translation tendencies, with neither showing consistent superiority across all aspects. DeepL tends to produce more concise and conservative renderings and, in several instances, preserves elements of the source text more directly. ChatGPT tends to produce more explicit, descriptive, and expressive renderings; however, in some instances, these tendencies are accompanied by added information, shifts in perspective, or changes in the pragmatic function of the utterance. These findings suggest that greater naturalness and expressiveness do not necessarily indicate a higher degree of equivalence. In German translation learning, DeepL and ChatGPT can be used as supporting tools for comparing translation alternatives and developing students’ ability to critically evaluate translation choices.

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978

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999

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