Factors Influencing Student Outcomes in a Large, Online Simulation-Based Introductory Statistics Course

The demand for statistical knowledge and skills is growing in many disciplines, so more students are enrolling in introductory statistics courses (Blair, Kirkman, & Maxwell, 2018). At the same time, institutions are seeking course delivery methods that allow for greater flexibility for students, especially following the onset of the COVID-19 pandemic; therefore, there is more interest in the development and delivery of online introductory statistics courses. To address this, I collaboratively designed an online introductory statistics course which focuses on simulation-based inference for the University of Nebraska-Lincoln. The course design was informed by the Community of Inquiry framework (Garrison, Anderson, & Archer, 2000). The course is delivered asynchronously and has the capacity for high enrollment. Following the development of the course, I co-taught this course from Fall 2018 to Spring 2021 and recruited enrolled students to participate in my study. Participants granted research access to several components of their normal coursework and completed three surveys: Survey of Attitudes Toward Statistics (36-question version pre-test and post-test; Schau, 2003a, 2003b) and the Distance Education and Technological Advancements Survey (Joosten & Reddy, 2015). The primary goal of this study was to understand factors that influence student outcomes in this course. An intervention was designed to support the community of inquiry within the course and was implemented during Fall 2019 and Fall 2020. Using Bayesian hierarchical models, there was no evidence of an effect of the intervention on student outcomes. However, there were a variety of other self-reported factors that were found to be associated with student outcomes. The secondary aim of the study was to understand whether students\u27 attitudes toward statistics changed during the term; however, descriptive statistics suggest that students\u27 attitudes did not change during the term. To address some of the limitations of this study, future research could examine these research questions for simulation-based introductory statistics courses across multiple institutions. This study may help create recommendations for developing online introductory statistics courses. Adviser: Erin E. Blankenshi