An Analysis of Students’ Writing Ability in AI-Assisted Writing
The integration of Artificial Intelligence (AI) tools in writing instruction has garnered widespread attention; however, empirical evidence on the actual quality of student writing produced with AI assistance remains limited. This study aims to examine students' writing ability in AI-assisted writing products. This research employed a qualitative case study design. Data were collected through document analysis of narrative texts from five Grade XII students at SMAN 12 Sinjai, Indonesia. The analysis was conducted using Brown’s (2018) five-component framework, assessing content, organization, grammar, mechanics, and style. The findings revealed that students’ writing ability in AI-assisted contexts remains predominantly low. Only two students demonstrated Moderate ability, while the rest showed Poor ability across multiple components. Specific deficiencies included extreme repetition in content, lack of logical flow in organization, pervasive past tense errors in grammar, missing punctuation in mechanics, and severely limited vocabulary in style. The study concludes that a fundamental disconnect exists between AI use and writing quality, as students lack the foundational knowledge necessary to utilize AI tools effectively. These findings suggest that AI integration alone does not guarantee improved writing outcomes without corresponding foundational skill development.