We evaluated student (N = 1,361) interest and performance on student-AI co-authored math word problems. Performance matched or exceeded standard problems. Students rated peer-authored problems more often, especially when authorship was disclosed. Liking predicted first-attempt accuracy when problems required greater textual engagement, supporting interest-based context personalization.