أثر استخدام الذكاء الاصطناعي التوليدي على جودة الكتابة الأكاديمية: دراسة كمية بين طلاب وأساتذة العلوم الإنسانية والتقنية

Abstract

In light of the growing prevalence and widespread adoption of generative artificial intelligence (AI) tools among university students, this study seeks to provide a comprehensive and balanced analysis of both students’ and faculty members’ perceptions regarding the influence of such tools on the quality of academic writing.

By comparing perspectives across two contrasting academic domains—the humanities and the technical sciences—the study bridges a notable gap in the existing literature, addressing both the perceived benefits and potential drawbacks of generative AI integration in higher education contexts. A quantitative survey-based methodology was employed, involving a sample of 102 students and 21 faculty members drawn from three distinct colleges. Data were analyzed using descriptive statistics (means and standard deviations) and independent samples t-tests to determine differences across disciplines. Descriptive results indicated a strong consensus among students regarding the positive contribution of generative AI in enhancing fundamental writing competencies—such as structure, coherence, and organization of ideas. In contrast, faculty members expressed heightened concern about the possible erosion of analytical depth and intellectual rigor in students’ written outputs.

The t-test analysis revealed a single statistically significant difference between the two disciplines, specifically concerning issues of academic voice and intellectual identity. Humanities students reported a significantly greater sense of loss of personal expression and authenticity in their academic writing compared to their peers in the technical sciences, with a moderate effect size (Cohen’s d = –0.489).

Drawing on these findings, the study argues that the central challenge does not lie in restricting the use of generative AI tools, but rather in developing educational frameworks and institutional policies that safeguard epistemic authenticity, academic integrity, and individual expression, particularly in disciplines that privilege critical and reflective thinking. The study concludes with recommendations for the establishment of clear institutional guidelines and capacity-building workshops aimed at promoting responsible and ethical AI-assisted academic writing practices, a position that aligns with faculty members’ expressed viewpoints.