— AI is a Floor Raiser, not a Ceiling Raiser
Every day I am convinced that Software Engineering should be taught without AI. AI can give you answers to easy problems. But you won’t be able to create mental models of how things work, which will help you solve hard problems.
This next semester I am teaching a course on practices and tools in Software Engineering (my take will be inspired by MIT’s The Missing Semester). AI usage will be one of the topics, where we will explore MCP, IDE integrations and AI-assisted documentation.
But I have no idea how to write assignments for other topics. It is very likely that an AI will be able to complete the assignment without any human intervention. If students opt to do that (they will, that’s the faith I have in our grade-oriented system), they will not achieve the learning outcomes.
Students will question: if AI can do these tasks, why should we learn it? Well, math teachers in school still assigned me problems that machines could already solve by then. But creating mental models of how things work is essential in education.
Now the real question is about the incentives. We should assess whether students can use their mental models, and not whether they can solve the task. Especially with 100 students, where exams or take-home assignments are the norm.