Artificial intelligence in civil engineering education

Civil engineering is a multifaceted field that involves designing, constructing, and maintaining infrastructure and the built environment. However, there are notable complexities in civil engineering subjects that are challenging to be taught in the classroom. Although dealing with these complexities was once a challenge for engineers trained in traditional classrooms, artificial intelligence (AI) technologies now increasingly transform the contemporary classroom in terms of the curricula and pedagogy to provide a better educational outcome. AI has emerged as a powerful tool in numerous fields including civil engineering that can help design and optimize processes, predict the behaviour of materials, and enhance their performance. Integrating AI technologies into civil engineering education proposes a significant paradigm shift, offering novel approaches to teaching and learning in this critical field. This paper presents a thorough examination of the multifaceted applications of AI in civil engineering, encompassing structural health monitoring of civil infrastructure, smart infrastructure monitoring, geotechnical engineering, traffic management and transportation planning, environmental sustainability, building information modelling (BIM), condition and risk assessment, urban project and plan, and construction management. Through a systematic literature survey, we explore how AI algorithms, incorporating image processing, machine learning, and deep learning, reshape educational practices and prepare researchers for modern infrastructure development and management complexities. We discuss the transformative potential of AI in fostering experiential learning and promoting interdisciplinary collaboration. By synthesizing empirical evidence and best practices, this paper offers actionable perceptions for educators, policymakers, and industry stakeholders seeking to harness the full potential of AI in civil engineering education.