  The use of AI assistants, along with the challenges they present, has sparked
significant debate within the community of computer science education. While
these tools demonstrate the potential to support students' learning and
instructors' teaching, they also raise concerns about enabling unethical uses
by students. Previous research has suggested various strategies aimed at
addressing these issues. However, they concentrate on the introductory
programming courses and focus on one specific type of problem. The present
research evaluated the performance of ChatGPT, a state-of-the-art AI assistant,
at solving 187 problems spanning three distinct types that were collected from
six undergraduate computer science. The selected courses covered different
topics and targeted different program levels. We then explored methods to
modify these problems to adapt them to ChatGPT's capabilities to reduce
potential misuse by students. Finally, we conducted semi-structured interviews
with 11 computer science instructors. The aim was to gather their opinions on
our problem modification methods, understand their perspectives on the impact
of AI assistants on computer science education, and learn their strategies for
adapting their courses to leverage these AI capabilities for educational
improvement. The results revealed issues ranging from academic fairness to
long-term impact on students' mental models. From our results, we derived
design implications and recommended tools to help instructors design and create
future course material that could more effectively adapt to AI assistants'
capabilities.
