Course Materials Development (Tier 2)

Description

About ten instructors who attend the bootcamp will be selected to develop course materials in the Fall semester. They will be engaged in a semester-long collaborative endeavor to develop teaching and learning materials of Bayesian methods for undergraduate students in their disciplines that are at public dissemination quality. Instructors of similar STEM disciplines will be teamed up, and each team is mentored by one of the PIs. Depending on the instructor’s objective and their plan of introducing Bayesian methods in their undergraduate curriculum, we expect some to develop a Bayesian module to be part of an existing course while others to develop a full Bayesian course as part of their curriculum offerings.

Funding

Instructors selected to participate in course material development will be compensated with $1,500 each for their time and effort.

Application

All participants in the BATS Bootcamp in Summer 2024 are eligible to apply to Tier 2 by an application. The application is closed.

Schedule

The schedule of Tier 2 activities for the 2024 cohort can be found at this link.

Example Course Materials

The following are some of the teaching materials that Bayes BATS participants have developed.

Project Cohort Project Title Project Participants Materials
2023 Surprise!—They’re Different   Zachary del Rosario
Stefani Langehennig  
2023 POGIL-style activities: Introductions to Bayesian Statistics   Olga Glebova
Kaitlyn Fitzgerald   Angela Ebeling
2023 Bayesian Thinking: Course Materials for Bayesian Topics   Abraham Ayebo
Samantha Seals
Toni Sorrell  
2023 Introducing Frequentist and Bayesian Methods in Parallel in an Undergraduate Economics Statistics Course   Patricia Toledo  
2024 Introductory Bayes In Context   Adam Gilbert
Laura Lambert  
2024 Bayesian Thinking in BSMEs   Tom Keenan  
2024 An Introduction to Expressing and Updating Beliefs (No Programming Required   Adam Scharfenberger  
2024 Introduction to Statistical Storytelling: A 1-Week Module in Bayesian Thinking   Christopher Wolfe  
2024 A Gentle Introduction to Probability and Bayesian Statistics   Laurie Baker
Jim Scott