SECONDARY STUDENTS’ CYCLICAL SELF-ASSESSMENT PROCESS MEDIATED BY GRAMMARLY IN RECOUNT TEXT WRITING - Fajriati Astuti; Bambang Widi Pratolo (University of Kuningan, 2025)
This research examines the cyclical self-assessment process in an English language learning class facilitated by Artificial Intelligence (AI). Guided by the research question, “How did secondary students of writing proficiency participate in a repetitive self-assessment procedure in Writing with the assistance of Artificial Intelligence?” This research uses a narrative inquiry method to collect data from three middle school students with writing proficiency levels at Angkasa Adisucipto Yogyakarta High School. Data was collected through reflective notes and interviews. Thematic analysis was used to analyze the data. This research produced two critical findings. Initially, three middle school students with varying levels of writing ability participated in different phases of a self-assessment cycle, which was influenced by two main factors: their drive to learn and their belief in artificial intelligence (AI). The higher a high school student's level of motivation, the more likely they will actively seek outside input. Additionally, their belief in Automated Written Corrective Feedback (AWCF) and Automated Writing Evaluation (AWE) motivates them to participate in assessment and revision processes that facilitate a cyclical self-evaluation process to improve their learning outcomes. Artificial Intelligence (AI) has the potential to enable highly efficient iterative self-evaluation procedures with diverse functions. These findings imply that integrating AI tools like Grammarly in writing instruction can enhance self-assessment efficacy, but educators must address feedback literacy and the limitations of AI-generated feedback. Future research should explore larger sample sizes and diverse contexts to generalize findings. Keywords: English Learning; Artificial Intelligence; Self-Assessment; Secondary Students.