Exploring the Effects of Generative AI-Based Personalized Feedback for Enhancing Pre-Service Teachers' Teaching Competencies

This study aimed to develop personalized feedback using generative AI and apply it to pre-service teachers to examine their reactions and effects. For this purpose, the study utilized the generative AI ChatGPT to create three rounds of personalized feedback. The first feedback was tailored based on the diagnosis of teaching competencies, while the second and third feedback were customized for instructional plans written by pre-service teachers. These personalized feedback sessions were sequentially provided to a total of 40 pre-service teachers. The research results showed that learners generally perceived personalized feedback positively, indicating that the provided feedback was helpful for creating instructional plans or improving teaching competencies. However, some participants suggested that the feedback content was relatively general and expressed a desire for more specific examples tailored to their individual needs. Regarding the effectiveness of personalized feedback, the study confirmed improvement in teaching competencies related to instructional design and operational skills among pre-service teachers. This research is significant in providing specific applications of generative AI in the field of education at a time when its utility is increasing. However, the study has limitations as it only examined the results of teaching competency diagnoses in confirming the effectiveness of personalized feedback. Future research will aim to explore evaluation results for instructional plans and teaching demonstrations.