Blended Learning in Intermediate Applied Statistics

Abstract

Online resources for introductory statistics courses are popular, but there has been relatively less technological innovation in the second course in applied statistics. This session describes the results of a Mellon Foundation grant for Blended Learning in the humanities (yes, humanities!) awarded for an intermediate statistics course. I recorded and posted most of the course’s lecture material and a series of R tutorials tailored for my syllabus. I also developed new course modules focused on examples from the humanities. I will discuss the successes, challenges, and lessons learned from this approach, along with students’ reactions. The online lectures allowed a flexible class structure: for topics I chose to explain in person, the videos served as a course-specific recorded textbook. The videos included proofs omitted from live lectures that relied on more math and probability than assumed by the prerequisites. Other times, the videos created class time for new assignments designed to inspire conversation, creativity, and friendly competition. For example, students watched recorded lectures on non-parametric modeling and spent the corresponding class time using classification trees to predict the authorship of the anonymous Federalist Papers. Because of the flipped approach, students encountered basic tools of text analysis, discovered pros and cons of the modeling method, and observed variation across classmates’ strategies in a context where questions could be answered quickly by peers and the teaching staff. The online materials have also been used to reach out to students during wintersession and the summer, increasing the number of students exposed to statistics past the introductory level.

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Teaching a Flipped or Blended Course