Abstract

Generative Artificial Intelligence (GenAI) is transforming education, with assessment design emerging as a crucial area of innovation, particularly in computer science (CS) education. Effective assessment is critical for evaluating student competencies and guiding learning processes, yet traditional practices face significant challenges in CS education. These include the growing need for personalised evaluation amidst increasing enrolments, the intensive practice demands of programming courses, and the rapid evolution of curricula aligned with emerging technologies. This paper examines the transformative potential of GenAI tools in addressing these challenges within CS education. Through a scoping review of existing literature, we explore how GenAI can assist educators in collecting relevant assessment materials, automating exercise creation, optimizing code testing, providing interactive feedback, and leveraging learning analytics. By synthesizing evidence-based insights, this study highlights the practical applications of GenAI, demonstrating its capacity to enhance efficiency, personalization, and impact in assessment practices, ultimately advancing teaching and learning in the era of GenAI.