tl;dr: I tried out a modified Python lesson and I think it was successful at balancing learner motivation with teaching foundational (and sometimes boring) concepts.

In many ways, teaching Python to scientists is easier than just about every other audience. The learning objective is clear: write code to make my science more accurate, more efficient, and more impactful. The motivation is apparent: data is increasingly plentiful and increasingly complex. The learners are both engaged and prepared to put in the effort required to develop new skills.

But, despite all of the advantages, teaching anybody to program is hard.

In my experience, one of the most challenging trade-offs for lesson planners is between motivating the material and teaching a mental model for code execution. For example, scientists are easily motivated by simple data munging and plotting using pandas and matplotlib; these are features of the Python ecosystem that can convince …