S15: Methods for implementing active learning in hybrid and online statistics courses

Information

Active learning is an integral part of effective statistics courses, where students gain experience with and internalize course concepts by “doing.” This learning can support all possible learning objectives, such as how to perform analyses, how to talk about statistics, and how to interpret statistics in the literature. When full or partially online course formats are introduced, be they flipped classrooms, virtual meetings, or asynchronous, there are new opportunities and challenges for implementing active learning in the course. I will discuss the structure and implementation of different types of active learning supported by online learning tools in the classroom or asynchronously, including group practice sessions, discussion boards, collaborative keys, and guided practice problem sets. Although these methods are supported by literature, special care must be taken in their implementation. For example, when assigning a collaborative key, how should students be grouped, how much participation should be required, and when should participation deadlines be? Potential pitfalls in implementing these activities will be discussed, informed by student course evaluations and surveys from these tools being used across four different statistics courses (introductory statistics, advanced statistics, data management and visualization, and GIS mapping), of size 5 to 50 students, in an MPH program.