NSF Award
2416621
This project aims to serve the national interest by creating a sustainable, adaptable framework for fostering critical thinking and inspiring diverse learners in STEM. By bringing together passionate experts with high social impact projects, advanced and introductory students, and students from both theoretical and applied disciplines, the project is designed to bring together several proven approaches to inspire interest, persistence, and success across diverse populations of STEM learners. Advanced students from statistics and applied sciences study advanced statistical methods (4 credits), while meeting weekly with introductory students, who study persuasive data visualization (1 credit). This novel two-course cross-level structure aims to promote sustained interest across the years of undergraduate study and foster critical statistical thinking. The project includes joint course development by faculty from several disciplines, who can then rotate teaching, making the course available to all disciplines and maximizing use of teaching resources. The modular course structure is adaptable and expandable. The project plans to include a public website and annual workshops to more broadly share the approach and teaching materials.<br/><br/>The project plans to use substantive topics with social impact, near-peer mentoring, and relationship-rich cooperative learning to foster students' belonging, self-efficacy, and motivation for STEM: the mediators of STEM success and persistence, especially among underrepresented groups. Rich project work in a cooperative cross-disciplinary active learning environment is intended to foster learning of critical statistical thinking beyond rote thinking that is replaceable by generative AI. Faculty professional development and formative evaluation are designed to enhance the intervention and longitudinal mixed methods research will evaluate its effectiveness. The NSF IUSE: EDU 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.<br/><br/>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.
