This is a session of Topic 5: Statistics education in the workplace, government and across disciplines

Session 5G (Thursday 12th, 16:00-17:30,   Level 3 - Conference Room D)

Designing Collaborative and Tailored Training in Statistics and Data Science

Organizer

• Frauke Kreuter (United States/Germany) : Session chair

Abstract

Solid skills in statistics and data science are key for master level students and working professionals, no matter which field of application they are in. This often leads to a very heterogeneous set of students, challenging instructors to bring everybody onto the same page when analyzing data and working on research projects. This session will present three case studies in which students from different disciplines or with different statistical training are taught together. The case studies will showcase collaborative and modularized approaches that include peer-to-peer teaching, leveraging different skills within working groups, and other ways of bridging the knowledge gaps. Two of the three papers will discuss how they address these challenges in the context of international master programs.

Papers