Information Infrastructure for Society: Integrating Data Science and Social Science in Graduate Education and Workforce Development

Information Infrastructure for Society: Integrating Data Science and Social Science in Graduate Education and Workforce Development

This National Science Foundation Research Traineeship (NRT) award in the Innovations in Graduate Education (IGE) Track to the University of Maryland will pilot an innovative, cross-disciplinary curriculum that integrates Data Science with Social Science. The project will advance the scientific understanding of the dynamics of human behavior by integrating the toolkits and analytical frameworks developed by social scientists with the new types of data, models and tools developed in the fields of computer science and statistics. The curriculum provides an innovative approach to training students in the creative and scientific use of the growing number of available data. It covers all phases of a research project, addressing social issues including problem formulation, data collection, manipulation, processing, and analysis. The project pilots an innovative modular training program that is tailored to fill specific needs of both traditional and nontraditional graduate students, and provides direct pathways both to future employers and to advancement with current employers. The project advances the understanding of how best to train students and working professionals in the STEM fields, particularly social science. The project tests a pedagogical approach that has been successful in other areas, namely, modular "nano" classes that are focused on experiential learning based on specific social problems and feature peer-to-peer learning between persons in the social sciences and computer science. Because the projects and problems to be worked on within the nano classes are designed together with federal, state, and local agencies, students will have the opportunity test and showcase their knowledge to current and future employers. The effectiveness of the program is evaluated by analyzing the reactions of the participants to the material provided, learning outcomes in terms of improved qualifications, use of learned material in their respective jobs, effects upon job performance, and estimates of rate of return. The data curation, management, interrogation and integration tools are built into a data facility system, within which collaboration is fostered, and which can be replicated and used by other curriculum adopters. A series of small randomized experiments will allow the empirical test of learning modules and improve them based on the results. The overall result of the project can be adapted by institutions in the US, and a program of outreach activities with the institution's international partners will allow an even broader transfer. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The Innovations in Graduate Education Track is dedicated solely to piloting, testing, and evaluating novel, innovative, and potentially transformative approaches to graduate education.

September 2016 - August 2019
National Science Foundation
Total Award Amount: 

Principal Investigator:

Frauke Kreuter

Additional Investigators