Exploring the Educational Applications of AI-Based Feedback: Focusing on the Beginner Learner Corpus

This study examines the potential of utilizing natural language processing technology to provide objective and efficient feedback in Korean language classrooms through an automated feedback system. To validate the effectiveness of AI-based automated feedback, the study compared corrections made by human annotators with those generated by the AI model, GPT4, using a corpus of beginner Korean language learners. The results indicated high concordance rates between human and GPT4 corrections, with Level 1 accuracy at 85.71% and Level 2 accuracy at 84.07%. Corrections primarily focused on grammatical corrections, averaging 61%, while lexical corrections comprised about 39%. Corrections across various parts of speech, including nouns, verbs, and adjectives, were performed at similar rates by both humans and GPT4. However, GPT4 showed limitations in appropriately correcting errors that required contextual understanding. Despite these limitations, the AI-based feedback system can be an effective supplementary tool in educational settings. Teachers can reduce their workload and focus more on content and structural feedback, while learners benefit from real-time, personalized feedback that encourages self-review and improves language proficiency. This study underscores the importance of AI-based educational tools and emphasizes the need for an integrated approach involving teacher collaboration to continually enhance the AI-based feedback system.