Collaborative Research: Advancing Bayesian Thinking in STEM

Vassar College, Poughkeepsie NY

Investigators

Abstract

This project aims to serve the national interest by improving statistics instruction through a focus on increasing access to Bayesian methods. Dealing with the complexity of uncertainty is an important part of the scientific process. Like scientists, STEM students need to derive rigorous conclusions from data in their science practice. This project is based upon the premise that wider inclusion of Bayesian methods in STEM curricula can help students understand scientific uncertainty. To support the wider use of these methods, the project plans to build a community of STEM educators who can transform their courses by introducing new instructional materials for Bayesian methods. The project team intends to develop and offer a professional development program for STEM instructors from other institutions that focuses on the use and teaching of Bayesian methods. In addition, teams of instructors will be mentored by the project team in the development of instructional materials. The project will disseminate the instructional materials and project results to the science education community through social media, journal publications, and conference presentations. This goal of this project is to make Bayesian methods as accessible as possible at the undergraduate level through a cross-disciplinary curricular instructor capacity-building program for different STEM fields. Through recruitment of a diverse body of STEM instructors, the project will: 1) Increase the number of undergraduate students who understand Bayesian methods; 2) Enhance the capacity of STEM instructors in Bayesian methods through training and community building; 3) Develop and enrich teaching and learning materials that showcase the use of Bayesian methods in STEM fields. To achieve these objectives, the three collaborating institutions, University of California Irvine, Vassar College, and Duke University, will offer a week-long instructor summer training boot camp. By the end of the boot camp, it is expected that instructor participants will be comfortable using Bayesian methods in answering scientific questions, using appropriate software for teaching Bayesian methods, and designing classroom activities and assessments that support the learning of Bayesian methods. Selected instructors from the boot camp will be mentored by the project team in the development of Bayesian teaching and learning materials, specifically using scientific data from their fields. Using surveys and learning assessments, the project will assess the effectiveness of the summer boot camp. The NSF IUSE: EHR Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This project is also supported by the NSF IUSE:HSI program, which has the goals of enhancing the quality of undergraduate STEM education, and increasing the recruitment, retention, and graduation rates of students pursuing associate’s or baccalaureate degrees in STEM. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.