Redesigning Assessment in Technical Education Amid Generative AI Disruption: A Call for Policy and Pedagogical Reform

Abstract

The rapid rise of generative artificial intelligence (AI) tools such as ChatGPT and Gemini has introduced new complexities to academic assessment, particularly in technical education where skill-based evaluations are central. This study investigates how generative AI is impacting assessment practices in technical education institutions across the Gulf Cooperation Council (GCC) region. Employing a convergent mixed-methods approach, the research draws on survey responses from 120 students and faculty members, as well as in-depth interviews with academic staff from three GCC countries. Quantitative findings reveal a significant disparity in AI tool usage between students and faculty, with students more frequently relying on AI for academic tasks. A chi-square test confirmed that this difference is statistically significant (χ² (3, N = 120) = 11.73, p = .008). Qualitative analysis identified four key themes: rising concerns over AI-enabled academic dishonesty, perceived threats to fairness and learning outcomes, institutional policy gaps, and emerging assessment adaptations such as oral exams and reflective evaluations. This study underscores an urgent need for institutional reforms, including AI-specific academic integrity policies, faculty training, and assessment redesign. By aligning pedagogy and policy with the realities of AI-integrated learning environments, technical education institutions in the GCC can uphold academic standards while fostering ethical, future-ready learning ecosystems.