This study investigates how AI feedback learning activities in English writing classes affect university students’ English achievement and writing motivation. It examines both cognitive and affective outcomes in EFL contexts using generative AI tools such as ChatGPT. A total of 244 first-year university students completed four writing tasks incorporating AI feedback during the revision process. Pre- and post-tests were conducted along with the Oxford Placement Test (Syndicate, 2001) and a modified version of Payne’s (2012) Academic Writing Motivation Questionnaire. Quantitative analyses revealed significant improvement in English achievement and three motivational subcomponents—enjoyment, recognition, and effort—while instrumentality showed no significant change. Qualitative analysis of open-ended questionnaire responses indicated that students valued AI feedback for error detection, coherence, and self-directed learning, yet recognized limitations such as unnatural expressions, misinterpretations, and overreliance on AI. The findings highlight the importance of AI literacy and propose a hybrid feedback model integrating AI and teacher guidance to enhance learner autonomy and writing competence.

1. 서론
2. 이론적 배경
    2.1. AI 기반 영어 교육
    2.2. AI 기반 영어 쓰기 피드백
    2.3. 영어 쓰기 동기
3. 연구 방법
    3.1. 연구 대상
    3.2. 연구 절차
    3.3. 데이터 수집 및 분석
4. 연구 결과
    4.1. 성취도 효과성
    4.2. 영어 쓰기 동기
    4.3. 학습자의 AI 피드백 학습활동 경험
5. 논의 및 시사점
REFERENCES

• 황은경(Professor, Bangmok College of General Education, Myongji University) | Eunkyung Hwang
• 임희주(Professor, College of Liberal Arts, Dankook University, 119 Dandae-ro, Dongnam-gu, Cheonan-si, Chungnam 31116, Korea) | Heejoo Im Corresponding author
• 손희정(Professor, College of Liberal Arts, Dankook University) | Heejung Son