Date
Publisher
arXiv
With the rapid rise of generative AI in higher education and the
unreliability of current AI detection tools, developing policies that encourage
student learning and critical thinking has become increasingly important. This
study examines student use and perceptions of generative AI across three
proof-based undergraduate mathematics courses: a first-semester abstract
algebra course, a topology course and a second-semester abstract algebra
course. In each case, course policy permitted some use of generative AI.
Drawing on survey responses and student interviews, we analyze how students
engaged with AI tools, their perceptions of generative AI's usefulness and
limitations, and what implications these perceptions hold for teaching
proof-based mathematics. We conclude by discussing future considerations for
integrating generative AI into proof-based mathematics instruction.
What is the application?
Who is the user?
Who age?
Why use AI?
Study design
