The Efficacy of English Academic Writing Improvement of Doctoral Students of Humanities and Social Sciences in China - Huang, Yuwei; Liang, Xiaohui; Li, Chang (Forum for Linguistic Studies, 2025)
Over the past 30 years, the expansion of doctoral student enrollment in China has led to a substantial increase in the number of doctoral students specializing in the humanities and social sciences. Nevertheless, the majority of these students predominantly publish in Chinese-language journals, which often results in a deficiency in their ability to write English academic writing. Consequently, identifying efficacious strategies to enhance their English academic writing proficiency is imperative. The emergence of AI tools has introduced both challenges and opportunities for students and educators in writing training. This paper aims to investigate the differentiation in writing feedback provided by AI systems versus human instructors for the group’s English academic writing. The findings indicate that the group demonstrates a greater engagement with AI-generated feedback compared to that provided by human instructors. Analysis revealed that human instructors delivered feedback characterized by greater Accuracy and Essential Feedback (p = 0.023 < 0.05; p = 0.013 < 0.05), whereas AI feedback excelled in offering clearer Direction for Improvement and a more Supportive Tone (p = 0.000 < 0.05; p = 0.009 < 0.05). No statistically significant disparity was identified between AI and human instructors concerning Criterion-Based Comments (p = 0.323 > 0.05). Based on these empirical findings, this paper proposes recommendations for integrating AI and human instructor feedback mechanisms, aiming to enhance the English academic writing skills of doctoral students, a substantial demographic within China that exhibits an urgent need for such training.