Chapter 2. Corrective Feedback in the Age of AI
Rob Hirschel and Kayoko Horai
Abstract
One of the most time-consuming and challenging aspects of being a language teacher is giving grammatical corrective feedback (CF) on writing. Many students expect to receive such feedback, and many teachers feel a strong obligation to provide CF on written work. Concerns surrounding CF include the possibility of demoralizing students, inconsistency and ineffectiveness, and the possibility that teacher time and effort are wasted when students do not pay attention. Traditional CF from the teacher has also generally required at least a day for teachers to mark the writing and return it to students, an undesirable delay that may miss a teachable moment when the student is focused on sentence construction. Finally, traditional teacher-generated CF is usually in the target language, a language that may not be comprehensible to students.
With the assistance of generative AI, however, it is now possible to provide CF to students instantaneously, in their native language, with great consistency, and with no teacher effort in marking. In this chapter, the authors demonstrate how individualized CF is now being provided to students in their native Japanese immediately upon submission of an assignment. Pedagogically appropriate activities related to the feedback are also discussed. The authors explore how generative AI provides new opportunities that include customized practice exercises informed by each student’s level and needs. Finally, the authors describe where the modern teacher and /or materials developer’s time and effort do come into play: prior to the assignment, in the careful construction of prompts.
About the Contributors
Rob Hirschel is an associate professor at the Sojo International Learning Center (SILC) of Sojo University in Kumamoto, Japan. He teaches general English communication courses as well as English-medium courses focused on cultural awareness and sports. He has enjoyed teaching both in Japan and in the US at various levels, ranging from pre-school to post-graduate. His research interests include CALL, intercultural education and vocabulary acquisition.
Kayoko Horai is a professor at the Sojo International Learning Center, Sojo University in Kumamoto, Japan. She teaches English communication and test-preparation courses while serving as a principal advisor at the Self-Access Learning Center, supporting students’ autonomous language learning. Her research focuses on English education, learner autonomy, and supportive learning environments for university students. She has recently been exploring the potential of generative AI to enhance individualized and self-directed learning.
Citation
Hirschel, R., & Horai, K. (2026). Corrective feedback in the age of AI. In R. Dykes, O. Edwards, D. Bollen, & T. S. W. Lin (Eds.), Artificial intelligence in Japan’s language learning classrooms (pp. 33–53). Candlin & Mynard. https://doi.org/10.47908/45/2
One of the most time-consuming and challenging aspects of being a language teacher is giving grammatical corrective feedback (CF) on writing. Many students expect to receive such feedback, and many teachers feel a strong obligation to provide CF on written work. Concerns surrounding CF include the possibility of demoralizing students, inconsistency and ineffectiveness, and the possibility that teacher time and effort are wasted when students do not pay attention. Traditional CF from the teacher has also generally required at least a day for teachers to mark the writing and return it to students, an undesirable delay that may miss a teachable moment when the student is focused on sentence construction. Finally, traditional teacher-generated CF is usually in the target language, a language that may not be comprehensible to students.
With the assistance of generative AI, however, it is now possible to provide CF to students instantaneously, in their native language, with great consistency, and with no teacher effort in marking. In this chapter, the authors demonstrate how individualized CF is now being provided to students in their native Japanese immediately upon submission of an assignment. Pedagogically appropriate activities related to the feedback are also discussed. The authors explore how generative AI provides new opportunities that include customized practice exercises informed by each student’s level and needs. Finally, the authors describe where the modern teacher and /or materials developer’s time and effort do come into play: prior to the assignment, in the careful construction of prompts.
About the Contributors
Rob Hirschel is an associate professor at the Sojo International Learning Center (SILC) of Sojo University in Kumamoto, Japan. He teaches general English communication courses as well as English-medium courses focused on cultural awareness and sports. He has enjoyed teaching both in Japan and in the US at various levels, ranging from pre-school to post-graduate. His research interests include CALL, intercultural education and vocabulary acquisition.
Kayoko Horai is a professor at the Sojo International Learning Center, Sojo University in Kumamoto, Japan. She teaches English communication and test-preparation courses while serving as a principal advisor at the Self-Access Learning Center, supporting students’ autonomous language learning. Her research focuses on English education, learner autonomy, and supportive learning environments for university students. She has recently been exploring the potential of generative AI to enhance individualized and self-directed learning.
Citation
Hirschel, R., & Horai, K. (2026). Corrective feedback in the age of AI. In R. Dykes, O. Edwards, D. Bollen, & T. S. W. Lin (Eds.), Artificial intelligence in Japan’s language learning classrooms (pp. 33–53). Candlin & Mynard. https://doi.org/10.47908/45/2
Information About the Book
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Title: Artificial Intelligence in Japan’s Language Learning Classroom
Editors: Robert Dykes, Oliver Edwards, Dave Bollen, and Tina Shu-wen Lin Publication date: June 2026 Read more... |