Jennifer Preciado Perez,

Title:

Student Perceptions of AI-Generated and Teacher Feedback in L2 Spanish Writing.

Abstract:

Providing effective feedback on student writing is a central challenge in second language (L2) instruction. While teacher feedback is widely used, it is often limited by time constraints, and students may not always fully understand or use it during revision. At the same time, artificial intelligence (AI) tools such as ChatGPT are increasingly being used to generate writing feedback, but it remains unclear how students perceive this feedback compared to that of their instructors.
This study explores how university-level learners of Spanish as a second language perceive and use feedback provided by both their teacher and an AI tool. Using an action research approach, data were collected from nine students through writing tasks, revised drafts, questionnaires, and interviews. The study also includes a detailed case analysis of how one student incorporated feedback from both sources.
The findings show that students do not view AI and teacher feedback as competing alternatives, but rather as complementary. Teacher feedback was valued for being clear and easy to follow, while AI feedback was appreciated for providing more detailed explanations. Regardless of the source of feedback, students tended to focus on correcting simpler errors and were less likely to revise more complex issues related to meaning.
These results suggest that AI can be effectively used as a complementary tool to support teacher-provided feedback, contributing to a more balanced and enriched feedback process.