Does hybrid feedback foster L2 writing development?

Feedback is a pivotal component of both L1 and L2 students’ writing development (McCarthy et al., 2022), but providing in-depth feedback is a labour-intensive process (Godwin-Jones, 2022). Recent developments in gener‐ ative artificial intelligence (GenAI) have increased interest in its use for providing personalized and real-time feedback in second language (L2) writing instruction. However, there is limited research on how GenAI-feedback combined with teacher mediation/control may support L2 writers’ development over time. Therefore, this study aims to investigate whether such hybrid feedback triggers the development of linguistic complexity in L2 writing.The study was conducted in a 15-week undergraduate Writing Skills course at a medium-sized university in Türkiye. Participants were 19 native Turkish students from the Department of English Translation and Interpret‐ ation with A2-level English proficiency. During the course, they completed eight timed, paragraph-level writing tasks across multiple genres, such as opinion, definition, process, and narrative, without technological support. After each task, students typed their drafts into shared Google Docs. They then received hybrid feedback: First, the course lecturer used GenAI (ChatGPT) to receive structured feedback focusing on the quality of the topic sentence, three common linguistic errors, three common global errors, and a fully revised version of the paragraph. Second, the course lecturer reviewed the GenAI-generated feedback and selected only accurate and appropriate responses, which were then shared with the students. Also, students wrote short reflection reports explaining how they engaged with the feedback and which suggestions they focused on. The dataset includes students’ original writing tasks, the hybrid feedback, and the reflection reports.The data analysis is still ongoing and focuses on analysing the linguistic complexity, considering both lexical and grammatical aspects (Bulté & Housen, 2012). To this purpose all text versions have been processed with the NLP tools for the Social Sciences (https://www.linguisticanalysistools.org/) and by selecting only those measures which are theoretically relevant (Bulté et al., 2025). By adopting a longitudinal perspective, this study aims to examine patterns of development rather than one-time improvements. Overall, this study contributes to discussions on the pedagogical efficiency of hybrid feedback in L2 writing instruction.