Author(s):
Need: College algebra – the most common general education mathematics course – has high failure rates and is a barrier to graduation for many students. Non-STEM students often have a terrible history with math and consequently have low interest and low confidence. STAT 1100: Data Literacy and Visualization was developed as an alternative; it integrates service learning and data science into a gen ed math course. Students learn basic statistics, data organization and manipulation, and appropriate visualization techniques. Mastery is demonstrated in a community-engagement project: small groups analyze data to communicate answers to questions posed by non-profit partner organizations.Guiding Question: What is the impact of STAT 1100 on students who enroll, in terms of learning, interest, confidence, and ability to pass.Outcomes: STAT 1100 has the highest pass rate of any gen ed math course at our university. Final projects, in which students analyze data to answer questions for local community partners, demonstrate students’ ability to analyze data and communicate results. Students’ confidence in their ability to do math significantly increases. Interest in math does not significantly change. Broader Impacts: The projects have two positive outcomes. First, they support and increase capacity in the community partners. Partners have used project results for program evaluation purposes and to identify new opportunities. Multiple organizations have asked to return as partners in subsequent semesters, demonstrating the value they find in participate. Second, this course increases the data literacy of non-STEM students, particularly their capacity to analyze and communicate data. Most students are from social science majors such as journalism, communication, and psychology, disciplines in which these skills are critical. We have anecdotal evidence of students using these skills in the workforce, such as a student who was hired directly by one of the community partners to continue the analysis begun in the course project. We also are working to disseminate the course model, and support other institutions who want to implement STAT 1100.
Coauthors
Betty Love, University of Nebraska – Omaha; Becky Brusky, University of Nebraska – Omaha; Andrew Swift, University of Nebraska – Omaha; Mahbubul Majumder, University of Nebraska – Omaha
