Leveraging Mathematical Knowledge to Prepare Future Math Teachers to Teach Data Science

Multiple professional societies – including mathematics, statistics, and mathematics educators – have recently released statements in support of teaching data science (DS) at the secondary level. Such statements implicitly (if not explicitly) seek preparation of teachers to deliver DS content. We present our experiences in developing, delivering, and refining curriculum which endeavors to prepare pre-service mathematics teachers to deliver this content. Our curriculum takes the form of a 5-week self-contained module that is delivered within coursework taken by pre-service mathematics teachers at the University of Northern Iowa and Iowa State University. We describe this curriculum, together with our inspiration and sources for this curriculum, as well as the design choices we made in its preparation. After offering the curriculum over 3 iterations – each of which were refinements of prior implementations – we have arrived at two themes that we think are foundational to preparing mathematics teachers to teach DS. These two themes are: 1) we can leverage future mathematics teachers’ prior mathematical knowledge to master DS concepts, and 2) we can illustrate challenges to DS methodology through a mathematical framework. We conclude with a description and rationale for those two themes.