Preparing Graduate Students for Careers in Teaching Statistics and Data Science

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The one-day workshop, "Preparing Graduate Students for Careers in Teaching Statistics and Data Science", will be held Saturday, July 28, 2018 in conjunction with the Joint Statistical Meetings in Vancouver, British Columbia. The workshop will provide graduate students and post-doctoral researchers with the tools necessary to develop innovative and pedagogically-sound learning experiences for their students, both inside and outside the classroom, and to implement formative and summative assessment to guide instructional practice. The ultimate objective of this workshop is to increase the proportion of successful instructors who have the skills, capacity, and inclination to take on the challenges of complex data-oriented teaching. Existing guidelines provide research-based recommendations for the pedagogy and assessment in introductory statistics courses. Ongoing efforts focus attention on modernizing the content and extending these ideas throughout the undergraduate curriculum. There has also been tremendous activity in developing materials for bringing principles of data science into stand-alone courses for broad student audiences, as well as using data-centric approaches in many types of statistics courses. The goal of this workshop is to equip future educators with concrete information ranging from recommended practices in teaching statistics and data science, to providing repositories of teaching and data resources, and creating the infrastructure knowledge necessary to seamlessly incorporate computing into the curriculum. Discussions will include decisions involved in developing curriculum, creating an assessment plan, and choosing technology tools. Workshop attendees will work through several examples and gain first-hand experience with active learning, use of real data, and technology tools such as RStudio and RMarkdown. More information can be found at the workshop website https://sites.google.com/view/preparetoteach/homeThis award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.