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

Jesse D. Troy, Megan L. Neely, S. Grambow, Gina‐Maria Pomann, Gregory P. Samsa
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Abstract

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.
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生物统计学硕士课程中的编程课程回顾
对于在医学和公共卫生领域跨学科科学团队中工作的合作型生物统计学家来说,计算是一项核心能力。然而,计算是一个广泛的领域,包含许多基本的教学结构和亚专业主题,并非所有这些都与执业生物统计学家相关。此外,计算在生物统计中无处不在,而为支持学生对生物统计亚专业的兴趣,计算教育也需要有所变化,这给课程设计带来了挑战。具体来说:在哪里以及如何将计算培训纳入生物统计学教育计划?我们在此讨论我们对这些问题的回答,因为它与两年制、全日制、强化生物统计学硕士学位课程有关。具体来说,我们定义并合理解释了指导我们课程设计的核心教学结构--计算思维,然后讨论了我们在计算方面培训生物统计学硕士生的两方面方法:开设两门系列课程,有针对性地进行计算培训;在课程的其他课程中嵌入计算培训。在详细介绍课程设计的同时,还介绍了我们的教学方法,包括我们如何评估学生的表现。
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