A Curriculum Review of Programming Courses in a Master of Biostatistics Program

Computing is a core competency for collaborative biostatisticians, who work on interdisciplinary scientific teams in medicine and publich health. However, computing is a broad field that encompases many underlying pedagogical constructs and subspeciality topics, not all of which are relevant for practicing biostatisticians. Furthermore, the ubiquitous nature of computing in biostatistics and the variation in computing education required to support students’ interests in biostatistics subspecialities presents a challenge for curriculum design. Specifically: where and how to integrate training in computing into biostatistics educational programs? We discuss here our answer to these questions as it relates to a 2-year, full-time, intensive master’s degree program in biostatistics. Specifically, we define and rationalize the core pedagogical contstruct that guided our curriculum deisgn—computational thinking—and then discuss our two-fold approach to training biostatistics master’s students in computing: creation of a 2-course series of targeted training in computing, and embedding training in computing throughout other courses in the curriculum. A detailed description of the course design is included along with a description of our instructional methods, including how we evaluate student performance.

Duke Scholars

Author Megan Lee Neely Biostatistics & Bioinformatics, Division of Biostatistics

Author Jesse David Troy Biostatistics & Bioinformatics, Division of Biostatistics

Author Gina-Maria Pomann Biostatistics & Bioinformatics, Division of Biostatistics

Author Steven C. Grambow Biostatistics & Bioinformatics, Division of Biostatistics

Author Gregory P. Samsa Biostatistics & Bioinformatics, Division of Biostatistics