Abstract:

The increasing use of artificial intelligence tools in language education has created new opportunities for the assessment of student writing. This study explores the potential of artificial intelligence in evaluating writing performance in German for Specific Purposes in first-year medical students), who achieved language proficiency levels ranging from B1 to C1 according to the Common European Framework of Reference for Languages. The research focuses on the comparison of three original academic essays written by medical students in German (Texts A) with their machine-translated versions produced by two widely used translation systems: DeepL (Texts B) and Google Translate (Texts C).

The study examines linguistic accuracy, medical terminology, grammar, and academic discourse across the three sets of texts. All versions were subsequently evaluated using the free version of ChatGPT, which served as an analytical tool for identifying similarities, differences, and recurring linguistic patterns in the students’ writing and the translated outputs. The comparison allowed for the identification of changes introduced by machine translation and provided insights into how artificial intelligence tools interpret and reproduce specialized academic language in the medical field.

The findings suggest that while machine translation systems can improve grammatical accuracy and lexical precision in some instances, they may also alter stylistic features and the intended meaning of the original texts. The use of artificial intelligence for evaluative purposes demonstrates potential as a supplementary tool in the assessment of student writing, particularly in German for Specific Purposes contexts. At the same time, the results highlight the importance of critical evaluation when integrating artificial intelligence tools into academic writing assessment.

The study contributes to the growing discussion on the role of artificial intelligence in language education and offers preliminary insights into its application in the assessment of medical students’ academic writing.

Keywords:

German for Specific Purposes, Automated assessment, ChatGPT, Tertiary education, writing skills, academic discourse.