Collaborative Research: CUE-T: Broadening Participation in Computing via Active Learning Strategies in Multi-Institution Online Synchronous Learning Environments

Due to the COVID pandemic, most U.S. Institutions of Higher Education (IHEs) transitioned in-person classes to online classes. Such a transition provides fertile ground for research into improving undergraduate STEM education in computing fields, specifically in broadening participation for underrepresented students and improving learning outcomes. There are ongoing challenges in attracting and retaining students to computing. This project intends to explore the impact of combining effective active learning approaches in computing courses in online synchronous learning environments (OSLEs) across multiple institutions with a Learning Assistant model. The proposed approach has the potential to improve student learning outcomes and retention rates in computing. This project's primary goal is to explore the impact of integrating effective active learning approaches in computing OSLEs and sharing resources across multiple institutions on students' learning outcomes, engagement, and retention. The project team plans to use a mixed-methods experimental design to investigate four research questions focusing on conducting professional development, using active learning approaches on student learning outcomes and retention rates, and sharing courses across institutions. This project will be conducted at six institutions, including two Hispanic Serving Institutions, two Historically Black Universities, and two small universities. This proposed project has the potential to significantly pathways for computing in both academia and industry. 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.