Student Perceptions on Reproducible Research in Introductory Statistics Courses

By Nicholas Bussberg (Elon University)


Reproducibility is an increasingly common requirement for quantitative research, both within and outside of academia. However, there is comparatively little research on how to implement reproducibility into quantitative curriculum. During the Fall 2021 and Spring 2022 semesters, I incorporated a flexible approach to include reproducibility in introductory statistics courses. My goal is to provide instructors from many quantitative disciplines, teaching with different software and at different levels, accessible strategies to teach reproducibility in undergraduate programs. This poster will present IRB-approved data on my students’ perceptions of reproducibility from Fall 2021 and Spring 2022. This work was conducted at Elon University, a mid-sized private institution, where I taught two sections of the intro course with 30 students in each section. The introductory course is required for many majors on campus but does not require previous statistics coursework. SAS is used as the software to conduct statistical analyses. The student perception data will provide insight into whether students from many backgrounds were receptive to learning about reproducibility in the classroom and thought the techniques that were presented were useful in creating reproducible research.


Student Perceptions on Reproducible Research in Introductory Statistics Courses.pdf