A Comprehensive Review of Artificial Intelligence in Civil Engineering Education

Artificial intelligence (AI) is reshaping civil engineering (CE) education by enabling adaptive, personalized, and efficient learning environments. Intelligent Tutoring systems (ITS), large language models (LLMs), and AI-based simulations are being increasingly utilized to enhance student learning in structural analysis, geotechnical engineering, hydraulics, and construction management. Each technology, however, presents distinct limitations, such as constrained flexibility, high development costs for ITS, and concerns regarding the accuracy, transparency, and ethics of LLMs. This study systematically reviews 82 peer-reviewed publications to identify the primary benefits and challenges of ITS and LLMs in CE education and to evaluate how their integration may address gaps in the current educational tools. The findings indicated that ITS provide structured instruction, learner modeling, and automated assessment, while LLMs are effective in natural language explanation, content generation, and on-demand learning support. Integrating the systems yielded advantages, including more reliable feedback, enhanced engagement, scalable learning, and improved equity. This study proposes an integrated ITS-LLM framework tailored to CE education and emphasizes the necessity for future classroom-based assessments to ensure responsible, effective, and sustainable AI adoption by civil engineering programs.