Providing Equitable Access to Fundamental Data Analytical Skills for STEM Students with a Theme-Based Approach

With support from the Improving Undergraduate STEM Education: Hispanic-Serving Institutions (HSI Program), this Track 2 project aims to improve fundamental analytical skills for STEM students in a large classroom setting with significant enrollment of students from groups historically disenfranchised in STEM. In the data revolution era, increasing representation in the data science workforce from the full spectrum of diverse talent addresses a critical need for remaining globally competitive. Enhancing the learning of fundamental analytical skills such as those taught in introductory statistics courses attends to this need. While project-based curriculum has proven effective, its application in large class settings with significant enrollment of students from groups historically disenfranchised in STEM has not been adequately explored. The project will utilize a theme-based approach to deliver a personalized learning experience. The primary objective is to transform introductory statistics into a subject that is engaging and meaningful for all students but attending to those aspects salient in highly diverse classroom settings. This project aims to enhance students' data literacy, broaden the potential data science workforce, and ultimately address the long-standing diversity gap. This project adopts a constructivist approach with theme-based data sets to foster conceptual understanding, lower the language barrier and reduce the readiness requirement in mathematics, and provide self-paced study materials with real-life examples to personalize learning experience. Centering efforts on the needs and preferences of students from groups historically disenfranchised in STEM, the project focuses on engaging student learning in a large class setting by using exercises with automatic feedback to accommodate students' busy working-learning schedules and cultivating a supportive environment with group study and personalized instructor support. Importantly, this approach establishes an active learning structure that can scale to benefit a diverse student population in classes with large enrollment. After designing and assessing the theme-based approach at the partner institutions, where over 1700 students are taught annually, the project team will disseminate theme-based learning materials across various platforms. Additionally, the project team will conduct online and in-person workshops, maintain a course website and establish a discussion forum to prepare and provide ongoing support for new faculty in implementing the theme-based model. This project is funded by the HSI Program, which aims to enhance undergraduate STEM education, broaden participation in STEM, and build capacity at HSIs. 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.