Building Social Science Data Analytics and Visualization Skills through Cross-Disciplinary Urban Research

Kean University, Union NJ

Investigators

Abstract

The primary goal of this research is to promote data analyze skills and apply data analytics to understand current urban issues in local and global communities. This project addresses the importance of digital literacy, the democratization of data knowledge, and cross-disciplinary collaborative research in the production of knowledge that is relevant to the communities served by public higher education. The project seeks to understand how cross-disciplinary research strengthens the understanding of the complexity of contemporary living in cities with an increasing use of digital technologies and platforms that inform the delivery of resources, services, and goods. This project fosters cross-disciplinary research by bringing forward discipline-specific skills in the social sciences and STEM via educational and research activities to develop data analytics and visualization tools to address socioeconomic, health, behavioral, social justice, and climate change challenges confronting urban communities. Thereby increasing the research and experiential capacity of faculty and students engaged in relevant and robust urban research supported by data analytics and visualization tools. The project utilizes a multi-method program evaluation approach to quantitatively and qualitatively study educational and research activities supported by the “Center for Data Analytics and Visualization in Urban Research.” Among the activities supported and evaluated are data analytics and visualization workshops and curriculum development, and faculty and student cross-disciplinary research. The research methods include surveys, informal and formal interview with The Center leadership, advisory board, faculty, and students to account for the multiple ways in which The Center’s offerings support digital literacy, knowledge management, and cross-disciplinary urban research at Kean University. 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.