This study investigates how artificial intelligence (AI)-generated and instructor-provided feedback interact within process-based, collaborative EFL writing to influence learners’ affective engagement, motivation, self-efficacy, and attitude toward writing. Semistructured group interviews with nine pre-service English teachers were analyzed using NVivo 14. Among the three categories, attitude, encompassing both positive and negative factors, was the most frequently observed, followed by self-efficacy and motivation. Positive attitude was linked to the convenience, immediacy, and personalization of AI feedback, and to the collaborative course design that supported iterative revision and peer learning. Negative attitude reflected concerns about AI overreliance, inaccuracies, and limited contextual appropriateness, particularly in ESPfocused writing. Regarding self-efficacy, instructor feedback provided deep, contextaware guidance, whereas AI feedback offered rapid, mechanical accuracy and motivational support. Confidence improved through safer drafting, metacognitive insight, and gradual mastery of AI utilization skills. Motivation was reinforced by the process-oriented structure, targeted instructor feedback, collaborative activities, and peer support that fostered engagement and improvement.

1. INTRODUCTION
2. LITERATURE REVIEW
    2.1. Affective Factors in Writing and the Need for Qualitative Inquiry
    2.2. Process-based Writing with AI and Instructor Feedback
3. METHODOLOGY
    3.1. Participants
    3.2. Procedure of the Writing Course
    3.3. Data Collection and Analysis
4. RESULTS
    4.1. Overall Trends
    4.2. Motivation-related Findings
    4.3. Self-efficacy-related Findings
    4.4. Attitude-related Findings
5. DISCUSSION AND CONCLUSION
REFERENCES
APPENDIX

• Unkyoung Maeng(Professor, Graduate School of Education, Ajou University, 206 Worldcup-ro, Yeongtong, Suwon 16499, Korea)