Unmasking the impacts of self-evaluation in AI-supported writing instruction on EFL learners’ emotion regulation, self-competence, motivation, and writing achievement

This study explores the impact of embedding self-evaluation within AI-supported writing instruction on learners’ cognitive emotion regulation, self-competence, motivation, and writing achievement. Conducted at a high school in Iran, the research utilized a quantitative quasi-experimental pretest-posttest design involving two intact pre-intermediate writing classes randomly assigned to an experimental group and a control group. The experimental group received instruction that combined AI tools with structured self-evaluation activities, whereas the control group followed a traditional teaching approach without AI integration or self-evaluation. Data were collected using the Cognitive Emotion Regulation Questionnaire, the Self-Competence Scale, the Academic Motivation Scale, and standardized writing assessments. Statistical analyses, including Chi-square tests and t-tests, indicated that the experimental group significantly outperformed the control group across all measured variables, demonstrating improvements in cognitive emotion regulation, self-competence, motivation, and writing achievement. These results underscore the value of integrating self-evaluation practices alongside AI tools to enhance learner outcomes in EFL writing contexts.