Analyzing Data for Local Non-profit Organizations

• In Event: Data Science as a Tool for Engaging in Civic Education

Abstract

Introduction & Significance
Many mathematics courses are abstract and divorced from real-world applications. Particularly for students who dislike math, topics such as algebra and geometry seem to lack utility and relevance to their current lives or imagined futures. Data literacy and visualization are critical literacies that are integral in many jobs, applicable far beyond data science careers (Brynjolfsson et al., 2011; Wolff et al., 2016) and provide alternatives to traditional mathematics approaches (Daro & Asturias, 2019).

Service Learning is a method of experiential education that combines classroom instruction with meaningful, community-identified service. It is a high-impact practice that increases student engagement (Kuh, 2008), provides authenticity, and increases critical thinking (Ash et al., 2005) and civic engagement (Westheimer & Kahne, 2003).

This study examines the intersection of data science and service learning; a course in which students learn basic data analysis and visualization, then apply those skills in order to answer data-driven questions for a community non-profit. It demonstrates the potential of such a course for impacting

Method & Data
Data for this study come from an undergraduate general education quantitative literacy course: Stat 1100: Data Literacy and Visualization. Over ten semesters, 222 students have engaged with 22 unique community partners including health-related organizations, local museums, and quasi-governmental organizations. The first ten weeks are focused on basic statistics and data visualization using Excel and Tableau. In the final six weeks, small groups of students collaborate to address their partner organizations’ questions through data analysis. Instead of a final exam, students present their findings to the partner. For example, students analyzed the administration of COVID-19 rent and utility assistance payments in Omaha, determining that they were equitably distributed in most cases (Figure 3.1).

Results
The students who enroll in this course are primarily social science majors, including sociology, journalism, and criminal justice. In some cases, the project has led to employment with the community partner, continuing to analyze data. In other cases, students have identified the utility of course material for their future careers.

Over 86% of students received grades of A, B, or C, the highest pass rate of any Gen Ed math course at UNO. Furthermore, the course has a significant impact on student attitudes, including significant improvements pre- to post-course in students’ mathematical self-efficacy and interest in math (p < .001), including agreement that STAT 1100 provides skills that will be useful in students’ future careers. In post-course focus groups and reflections, students report that the assignments were useful because it “didn’t feel like we learned things and then never had to use them again.” They express particular fondness for the project, calling it a “real life experience” that is “good experience for the workplace.” The students recognize the value they add to community organizations, including those whose missions are personally meaningful.

Authors

• Michelle Friend, University of Nebraska - Omaha

• Betty N Love, University of Tennessee

• Rebecca Brusky, University of Nebraska - Omaha

• Andrew Swift, University of Nebraska - Omaha