By Angela Ebeling (Wisconsin Lutheran College)
Information
The Bayesian framework for statistical decision-making is gaining prominence and can be more intuitive than traditional frequentist methods. However, frequentist approaches still dominate introductory statistics courses. To introduce Bayesian thinking, we developed a POGIL-style (Process Oriented Guided Inquiry Learning) activity where students engage in small-group, inquiry-based learning with the instructor as a facilitator.
This study examines student satisfaction and performance in learning Bayes’ Theorem with and without POGIL pedagogy, while also analyzing demographic factors such as gender and race. Using real-life examples, including playing cards and the ELISA test for HIV, students explore Bayesian concepts collaboratively.
The study was conducted at a small liberal arts college in the Midwest. In Fall 2024, the activity was used in two Elementary Statistics courses (MAT 117, ~30 students each) and one Biostatistics course (BIO 310, 9 students). Additional sections will be taught in Spring 2025 and Fall 2026, with some using traditional lecture-based instruction.
Preliminary findings suggest that female students in the upper-level biostatistics course reported higher satisfaction with group work and the POGIL structure than males, whereas in elementary statistics, gender differences in satisfaction were smaller. Further Bayesian regression analysis will provide deeper insight into differences in student experience and learning outcomes. Ultimately, this project aims to improve statistical and data science education by examining how different teaching approaches influence engagement and understanding.
Link to Google Drive folder with student and instructor versions of the activity as well as the satisfaction and demographic surveys.