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Abstract:
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After graduation, we expect our statistics and data science students to collaborate with various domain experts to understand and refine questions to be answered, to access and analyze the appropriate data, and to interpret and implement results and recommendations. Since collaboration is such a vital aspect of the work of most data scientists, professional skills should be taught in the curricula along with the myriad technical skills. However, including such instruction can be challenging.
In this poster, I will describe how I have structured an introductory data science course using the Team-Based Learning pedagogical strategies to teach students how to program in R; develop statistical thinking skills; and learn and practice collaboration skills. This approach can scale to large classes because of the extensive within-team discussion and collaboration, creating a small class atmosphere even in large classes. I will describe assessments from 3 semesters on the effectiveness of this approach; how to overcome potential barriers; tips for teaching data science, statistical thinking, and collaboration in the same course; and online resources for others to teach using this approach.
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