By Rachel Lobay (The University of British Columbia) and Lasantha Premarathna (The University of British Columbia)
Information
We will present on the design and classroom implementation of an interactive Bayes' Theorem lab in a large introductory statistics course (STAT 251) at the University of British Columbia. The project came about from student feedback where a clear desire for more structured, interactive support with Bayes' theorem and related probability concepts emerged. Therefore, we developed a new interactive app to target these problems. The app is intended to help students improve their understanding and connect conditional probability, the law of total probability, and Bayes' theorem and to be able to more confidently and independently solve problems on them. In terms of structure, the app is a self-paced game that focuses on constructing tree diagrams from scratch to connect the concepts. It is designed to be highly interactive and has low-stakes quiz-yourself questions along the way. In a class lab, the students were given individual access to the applet as well as a short in-lab assessment and post-lab survey that examined student performance and perceived understanding. Across the multiple lab sections, we found that the results suggest the app supported students who struggled with these concepts, while survey responses indicated high engagement and self-perceived improvements in understanding. Thus, our poster will describe the applet, lab structure, and results in more detail and show how such self-guided, active-learning tools can support connecting challenging topics and students' conceptual understanding in large introductory statistics courses. This activity was implemented at the University of British Columbia in a large introductory statistics course (with over 300 students) that is largely composed of second year engineering and science students.