Artificial Intelligence in the Evaluation of Academic Writing in Higher Education

Academic writing is central to higher education, yet marking large cohorts of academic writing essays remains time-consuming. Assessors must align each essay with rubrics and provide detailed feedback, often under significant time constraints. This study examines whether artificial intelligence (AI) can streamline assessment of academic writing essays. Thirty first-year academic writing essays were assessed independently by an AI system and two experienced markers according to the Common European Framework of Reference for Languages (CEFR). The qualitative analysis involved comparing the nature and quality of AI-generated feedback and human markers, while the quantitative analysis compared the CEFR levels assigned by AI with those from the human markers. Findings show strong agreement between AI and human markers on surface-level errors (e.g., grammar and mechanics) but low agreement on CEFR proficiency classification. AI therefore appears well-suited for initial screening and formative commentary in large classes, while final proficiency judgements should remain with humans. The study contributes to debates on integrating AI in higher-education assessment by showing how AI can complement—not replace—human judgement, improving efficiency without sacrificing feedback quality. This exploratory study offers valuable insights; however, future research is warranted for deeper understanding of how AI can be integrated into higher-education assessment.