AI and student assessment

Main, Paul (2025) AI and student assessment. International Journal of Science and Research Archive, 16 (2). pp. 305-313. ISSN 2582-8185

This article examines the transformative role of artificial intelligence (AI) in student assessment within contemporary educational settings. Drawing on current implementations across international education systems, we analyze how AI technologies are reshaping assessment design, administration, scoring, and feedback mechanisms. The paper explores key benefits including automated question generation, real-time monitoring, personalized feedback systems, and enhanced accessibility features. We address critical challenges surrounding academic integrity, algorithmic bias, and the balance between technological efficiency and human judgment. Through examination of case studies, including International Baccalaureate programs, we identify effective strategies for AI integration that maintain pedagogical integrity whilst leveraging technological advantages. Our findings suggest that successful AI implementation in assessment requires careful collaboration between educators and technologists, robust AI literacy development, and ethical frameworks that prioritize equity and fairness. The article concludes with recommendations for future directions in AI-driven assessment that support both individual learning needs and broader educational objectives.