Collaborative Keys to Improve Active Learning in Asynchronous Online Statistics Courses

Oregon Convention Center 

Room: CC-F150 

Active learning is an important part of statistics education, with consistent support in the literature and as included in the GAISE report. Learning-by-doing helps students gain the relevant knowledge and skills needed for statistics, as does working on problems with peers and the instructor. Asynchronous online courses were gaining in popularity before the COVID-19 pandemic, and are now a fixture in many academic programs. However, this format poses a challenge to active learning as it does not allow for formative feedback in real time.

One possible solution to this challenge that has gained prominence in recent years is the use of collaborative keys. Collaborative keys use a collaborative tool (e.g. GoogleDocs) as a platform for students to work together to create an answer key for any assignment. This involves students jointly generating and refining answers to the provided questions in the assignment (e.g., activity, homework).

There are many different ways in which collaborative keys can be adapted depending on the course and student population: group or whole class contributions, number of questions, number of students, instructor interaction, tracking contributions, and grading. This panel is composed of statistical educators who have experience using collaborative keys in different ways in their (virtual) classrooms, both at the undergraduate and graduate level and particularly in biostatistics, public health, and clinical research programs. In this session, they will share the success story of collaborative keys as an active learning approach as well as lessons learned. The goal of the session is to discuss and disseminate practical knowledge so attendees are able to implement collaborative keys in their own courses in a way that best fits their students' needs.

Format: Panel Discussion
Chair: Matt Hayat (Georgia State University)
Panelists: Ann Brearley (University of Minnesota), Steven Foti (University of Florida), Brandon George (Thomas Jefferson University), Michael Jiroutek (Campbell University), Laura Le (University of Minnesota)

Yes

Section on Teaching of Statistics in the Health Sciences

Business Analytics/Statistics Education Interest Group

Section on Statistics and Data Science Education