Designing a Large, Online Simulation-Based Introductory Statistics Course. Issue 1 (2nd January 2023)

• Record Type: Journal Article
• Authors: Burnham, Ella M.; Blankenship, Erin E.; Brown, Sydney E.
• Is Part Of: Journal of Statistics and Data Science Education. Volume 31:Issue 1(2023)
• Page Start: 66
• Page End: 73
• Publication Date: 2023-01-02
• Subjects: Asynchronous -- Distance -- Randomization
• DOI: 10.1080/26939169.2022.2087810
• Languages: English
• ISSNs: 2693-9169

Abstract

Abstract: We designed an asynchronous undergraduate introductory statistics course that focuses on simulation-based inference at the University of Nebraska-Lincoln. In this article, we describe the process we used to design the course and the structure of the course. We also discuss feedback and comments we received from students on the course evaluations, and we reflect on the course after teaching it for the past three years. Our goal is to provide useful tips and ideas for instructors who have developed or are developing their own asynchronous introductory course. While we emphasize simulation-based inference in our course, we believe that many of the design features of this course would be useful for those using a traditional approach to inference in their introductory courses. Supplementary materials for this article are available online.