Traditional undergraduate biology pathways often delay advanced mathematics, leaving students ill-prepared for the stochastic modeling and differential equations required in modern computational biology. Insights shared by the Society for Mathematical Biology emphasize that integrating data science early in the life sciences pathway drastically improves experimental design capabilities. In your experience, what are the primary pedagogical hurdles when co-designing foundational courses across biology and mathematics departments to better integrate mathematics into biology?
