Undergraduate Service Learning Experiences with Data: Mathematics in the Community

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This project aims to serve the national interest by transforming how undergraduate students engage with and learn mathematics in a new first-year general education (GenEd) course. In this course students will analyze and create visualizations of data in order to answer authentic questions from non-profit community partners. By developing data literacy and visualization skills critical in an information-dense society, students will meet general education requirements in quantitative literacy. Researchers expect that students will increase in confidence and interest in mathematics and data science. Meaningful interactions with community partners will enable students to develop an increased commitment to community engagement and enhanced workforce skills, such as: leadership, communication, and critical thinking skills. The course is also expected to engage students who may have lower interest and self-efficacy in mathematics, thus broadening participation in data science.The project aims to increase understanding of the effectiveness and feasibility of service learning as a context to improve student outcomes in GenEd mathematics courses. Service learning is a method of engaged teaching and learning that emphasizes critical thinking and problem solving by connecting course content with real-world experiences. Through inquiry-based learning the project will engage students in authentic inquiry, solving real-world problems and documenting learning through regular reflection. The project will investigate the educational impact of the GenEd course in terms of students’ interest and engagement in mathematics and other STEM disciplines. Retention in the university and future course-taking behavior will also be examined. A within-subject design will be used to measure how the course changes student attitudes towards STEM by having students complete a pre-course survey and a corresponding post-course survey using validated measures of self-efficacy, interest, and STEM attitudes. In addition, the research team will work with instructors of other GenEd mathematics courses to implement a between-subject design to compare courses. Comparisons will look both at absolute outcomes (e.g. comparing interest in future STEM-course taking at the end of the semester between each course) and also at changes from the beginning to the end of the semester (e.g. gains in mathematical self-efficacy). The team will apply a mixed-methods approach that uses quantitative data to measure progress towards participation targets and qualitative data that provides insights into the research questions as well as insights into the successes and challenges of the overall project. Data collection will consist of semi-structured interviews and focus groups, project documents, reflections, classroom observations, surveys, and university enrollment data. Project results and deliverables will be shared with other institutions through a public website as well as publications. 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 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.