Teaching Engineering through Murder Mysteries and Personalized AI Tutor

CE 357: Introduction to Geotechnical Engineering is a third year required undergraduate course that has traditionally been a challenging course for students due to its abstract nature. The average course rating for   CE 357 is 3.8 in the last twenty years. I have successfully transformed the lecture modules to achieve a significant increase in interest and students’ performance in the course. Although preliminary work looks promising, I want to scientifically evaluate the effectiveness of the course and publish the findings. Additionally, the weekly labs remain unchanged, which continues to be a challenge for the students, as it requires rote work and needs a reform. 70% of undergraduates in CE311K, Introduction to Numerical Methods, have no programming experience. More than 84% of the students who took CE 311K in 2022 do not think programming is necessary to be a successful civil engineer. This disconnect translates to the lack of adoption of data-driven techniques and computational methods in engineering, leaving petabytes of data untapped and limiting students’ potential as the next-generation workforce. On the other hand, AI models like GPT-4 can solve all programming tasks in CE 311K with 100% accuracy in seconds. The challenge is how to provide a better learning experience for students in introductory programming courses in the era of AI. I aim to tackle three main challenges: (i) how do we engage students in abstract programming concepts? (ii) how can we foster fundamental learning through AI assistance for students with diverse backgrounds? and (iii) how do we train students to use AI to solve complex problems critically?