Facilitator or thinking inhibitor: understanding the role of ChatGPT-generated written corrective feedback in language learning

Written corrective feedback (WCF) is crucial in foreign language learning, helping learners identify and rectify writing errors. However, manual WCF can be time-consuming for educators. Artificial general intelligence (AGI), exemplified by ChatGPT, offers a promising solution via automated WCF, addressing learners' intricate linguistic demands. While effective in English learning, the suitability of AGI-powered automated WCF for other languages with complex grammar remains uncertain due to the English-centric training of many large language models. This study examines the reliability and acceptance of ChatGPT-generated WCF within a German as a foreign language (GFL) context. Through a 200-essay analysis, we explore two questions: (1) How does ChatGPT-generated automated WCF compare to teacher-provided WCF? (2) How do GFL learners respond and interact with WCF from both sources? Our findings revealed different behavioral, cognitive, and affective engagements between ChatGPT-provided WCF and teacher-provided WCF. ChatGPT has greater potential for providing diverse lexical, grammatical, structural, and content feedback, facilitating GFL learning. However, students' emotional perceptions of ChatGPT-generated WCF vary, sometimes even negative, hindering language learning. We further explored the advantages and challenges of integrating ChatGPT-generated WCF into foreign language learning. Our findings underscore the potential of integrating AI-powered automated WCF into foreign language learning and writing development.