Enhancing Engagement in Civil Engineering Education Using AI-Based Tools: A Case Study in Hydrology and Open Channels Module

This paper presents a case study on the integration of generative AI-based online tools in a Hydrology and Open Channels module, a traditionally rigid and highly analytical course that has historically struggled with low student engagement, as reflected in prior feedback. To enhance engagement and improve learning outcomes among 36 Level 5 BEng Civil Engineering students, this study incorporates a multi-sensory learning environment with interactive generative AI tools to support diverse learning styles. These tools aim to address the engagement challenges faced by digital-native students, who are accustomed to fast-paced, bite-sized content. The results indicate positive feedback from students, who described the experience as innovative, memorable, and practical as well as significantly boosted student engagement and retention. However, challenges such as resource limitations, resistance to AI, and potential policy conflicts remain. Addressing these through including alternative engagement methods, and clear communication with university stakeholders will be essential for broader implementation and sustainability of AI-driven educational enhancements.