Evaluation and Analytics

You will find here links to the core program courses that I created as the founding director of the MS in Program Evaluation and Data Analytics at ASU. The “source code” for each of the classes is available on GitHub:

The Data Science for Public Service [DS4PS] site was created to highlight cases where technology, data and analytics are being used in the public and nonprofit sectors to provide career context for those interested in this emerging space.

All of the “source code” for the courses above, including lectures and labs, are included in the DS4PS GitHub repos. They have open source licenses and are available for use and adaptation.

Management

Data for the Public Good

Public agencies and non-profit organizations have begun to exploit open, mobile, and big data by harnessing advanced computational tools. Public agencies are increasingly interested in unlocking the potential of large-scale data to improve service delivery and inform policy efforts. Computational tools capable of making productive use of big data have proliferated in recent years, drastically decreasing the barriers to entry for interested parties. This course will explore techniques used for data extraction, analysis, and visualization. Students will operate as their own laboratory through a data journaling exercise, and devise strategies for incorporating data into management practices of public and nonprofit organizations.

Public Organizations and Management

This course introduces students to the study of organizations and management in the public sector. It is a required course and a building block for subsequent courses in management and policy implementation. It covers key management competencies such as strategic planning, performance management, incentives and human motivation, collaboration, and decision making.

Nonprofit Management

This course introduces students to the rich history of the nonprofit sector and modern management challenges that nonprofit organizations face.  The course will cover theories that guide research on nonprofits, important themes in nonprofit governance and leadership, and some specific case studies of nonprofit sectors such as international development and the environmental movement.  The course builds a foundation for future employment in the sector.

Data and Statistics

Intro. to Data Science for the Social Sector

Data science skills are in high demand. The course offers a practical, tools-based approach that is designed to build strong foundations for people that want to work as policy analysts or data-driven managers. Students will be introduced to the data science ecosystem, a growing set of integrated tools that streamline the analytical process and make it easier to share results in compelling formats. Familiarity with the ecosystem allows you to combine data and analysis in interesting and creative ways. There are currently over 200,000 open government datasets available online, and over 12,000 free analytical packages for R that allow you to use the data. Leveraging these resources, projects that previously would have taken months and can now be done in days. We will cover data programming in R, visualization, automated reporting, and data dashboards. No prior programming experience is assumed.

Program Evaluation

Program evaluation is a vast field that encompasses many different research traditions including case studies, process tracing, stakeholder analysis, causal modeling, and cost-benefit analysis.  The emphasis of this course will be on the quantitative modeling of program impact.  As such, the theme of unbiased results will be prominent throughout the course.  Students will learn how to think through causal modeling using correlation analysis (regression), and applying the appropriate techniques to limit bias (panel methods, instrumental variables, propensity score matching, regression discontinuity design, and natural experiments).  The course will also present a variety of research designs that allow for the isolation of program impacts from other factors that contribute to variation in program outcomes. The objective of the course is to give students the tools that they will need to be responsible producers and consumers of program evaluations.

Data-Driven Management in Public Organizations

This course introduces students to the field of performance management and the practice of data programming. It is a practical, tools-based course designed to build the foundations for strong data analysis as part of the performance management process. We will cover basic data operations, graphics, programming fundamentals, text analysis, and the creation of user interfaces. As part of the class students will work in a team to build a model performance management system that includes a data collection process, an analytical framework, and a dashboard to report key performance indicators to stakeholders. 

Public Policy

Urban Policy

Urban policy is an important topic that touches on many aspects of public policy because most people live, work, and play in cities or their surrounding suburbs. This course is designed to give a theoretical and policy context for students that wish to work in local government, the nonprofit sector, economic development, real estate, or related fields. The course covers: the social and economic benefits of urban regions, key causes and implications of urban sprawl and the urban / suburban divide, tools of urban policy and economic development, and spatial analysis. As part of the class students complete GIS labs to build a basic competency in spatial analysis.