By Ciaran Evans, Philipp Burckhardt, Rebecca Nugent, & Gordon Weinberg (Carnegie Mellon University)
Introductory statistics classes often serve a diverse population of students who take the class for a wide range of reasons. While in some cases all students do take the same course, it is common to have several different intro courses targeted at specific departments and majors. However, the statistical content of discipline-specific classes is often similar regardless of discipline. Recognizing these similarities in statistical material, our department is moving towards a hybrid approach, in which students from different backgrounds take the same introductory statistics course and attend the same lectures, but attend different labs and work with different class project datasets. This allows us to provide discipline-specific content to different lab sections, while teaching the same core material in lectures. Additionally, the use of general examples in lectures allows students from different backgrounds to see how course content can be applied to a range of areas, not just their own specialization. In this poster we report on our first semester piloting this approach, in which we develop specific lab materials and case studies for students from the biological and physical sciences.