Teaching Note—Data Science in the MSW Curriculum: Innovating Training in Statistics and Research Methods

ABSTRACT

Recent and rapid technological advances have given rise to an explosive growth of data, along with low-cost solutions for accessing, collecting, managing, and analyzing data. Despite the advances in technology and the availability of data, social work organizations routinely encounter data-related problems that have an impact on their opportunities for making data-driven decisions. Although training in research methods and statistics is important for social work students, these courses often do not address the needs organizations face in collecting, managing, and using data for data-driven decision making. In this teaching note, we propose innovating the social work curriculum using a data science framework as a way to address the day-to-day challenges organizations face regarding data. We provide a description of data science, along with four examples of MSW student projects that were based on a data science framework.

Additional information

Notes on contributors

Brian E. Perron

Brian E. Perron, PhD, is a professor at the University of Michigan School of Social Work. Bryan G. Victor, MSW, PhD, is an associate professor at the Indiana University School of Social Work. Barbara S. Hiltz, MSW, is a clinical assistant professor and director of the MSW program at the University of Michigan School of Social Work. Joseph Ryan, PhD,MSW, is a professor at the University of Michigan School of Social Work.