By Carolyn Cuff and Sam Hockenberry (Westminster College)
Information
Service learning projects (SLP) can be an excellent way for students in introductory statistics classes to be shown the data, work with real data, and experience messy data while simultaneously gaining insight into the critical role that statistics can play in small companies and community agencies. Often, these organizations do not have the time or the expertise to summarize data beyond basic single variable descriptive reporting. Implementing a SLP gives students the opportunity to work through the steps of a statistical analysis and see how useful even basic statistical knowledge can be. For the past four semesters, the Concepts of Statistics course at Westminster College has incorporated such a project. For two semesters, students worked with the directors of PA 2-1-1 Southwest. PA 2-1-1 Southwest is part of the national 2-1-1 call centers initiative. Specialists answer phone calls to the 211 number (an analog to 911) and then provide the callers with referrals to social service agencies including organizations which provide basic human needs resources, income tax services, and military veteran services. The focus of analysis in Spring 2017 was on the 12,000 contacts initiated by veterans and the 30 variables associated with each call including demographics of the caller, call origin location, and reason for call. Students sought to understand and summarize associations between variables collected during each call to provide 2-1-1 directors a deeper understanding of the communities they serve. This poster presents the timetable of this SLP and its relation to course content and to GAISE 2016; graphs students developed using StatCrunch and maps that a student doing an independent study in Big Data developed in R; and assessment details of the project. Handouts (also available as web links) include outlines of lessons learned from this project and other less successful projects (e.g. the role of the partner agency in success, student outcome measures), the pros and cons of working with such a large data set with students at this level (e.g. data cleaning vs. informative outliers), how to develop service learning partnerships, and a brief bibliography of SLP in the undergraduate classroom.