teaching
Course materials I have developed
SPIA 2005, 2006, 2104: Introduction to Urban Analytics
This is a course intended to give undergraduates an initial exposure to the tools and technical skills involved in “urban analytics,” as well as a foundation to understand the social and historical context of the urban data sets we are analyzing. Technical skills cover: analysis of tabular data using spreadsheet software (Excel, LibreOffice Calc), including use of VLOOKUP and pivot tables; Python scripting to do more complex data aggregation and programmatic data acquisition using APIs; and using multicriteria decision analysis tools. Social issues covered include:
- the manufacturing sector in post-industrial US cities
- policing pattern analysis
- gentrification
- vacancy
- environmental justice
- open government data
Course Textbook (under construction)
UAP 4854: Urban Infrastructure
This is a new course prep this coming year (2021) for me, so the details of this course are still in the works. A couple things for sure:
(1) I will try to expand students’ conceptualizations of what is “infrastructure” – to include social and ecological aspects of the system in addition to the technical aspects.
(2) I will place emphasis on the role of infrastructure in perpetuating social inequity (especially racial), and what future alternatives might look like
(3) I recently received a small grant to purchase a drone and thermal sensor to do some mapping of urban temperatures in Roanoke. We will do this to learn about the potential role of green infrastructure to mitigate urban heat island effect.
Course Schedule (Spring 2021), including links to slides, readings, and in-class activities
SPIA 4464: Data and the Art of Policy and Planning
In this course, students will explore the role of data and analytics in policy-making and planning processes. To what extent are big data and analytics improving our decision-making abilities, and in what ways may they be perpetuating entrenched social problems? Through analysis of current examples and cases, we will explore how we, as data-literate policy-makers and planners, can help influence the ways data is used, and how collaborative and participatory methods of decision-making can enhance policy and planning outcomes. The course will be divided into two parts: (1) Understanding the Present Landscape of Data, Modeling, and New Information Technologies; (2) Roles for Data in Policy-Making and Planning Processes.
(1) Understanding the Present Landscape of Data, Modeling, and New Information Technologies. In this part of the course, we will explore the rapid changes in types, velocity, and volume of data in recent years, and how this data relates to different kinds of models and technologies. We will examine the pros and cons of “big data” and the different perspectives around the effects of “big data” on society.
(2) Roles for Data in Policy-Making and Planning Processes. In this part of the course, we will explore the roles of policy-makers and planners in the age of “big data.” Here we will challenge the notion that “big data” renders theory irrelevant, cover how change is affected through the processes of policy-making and planning, and what data-based tools policy-makers and planners have at their disposal.
Course Schedule (Spring 2021), including links to slides, readings, and in-class activities