Current Course Offerings

Spring 2022


Core Competency 1: American Politics

PSCI 236 Public Policy Process

Julia Lynch (T 8:00 am - 10:00 am)

This course introduces students to the theories and practice of the policy-making process. There are four primary learning objectives. First, understanding how the structure of political institutions matter for the policies that they produce. Second, recognizing the constraints that policy makers face when making decisions on behalf of the public. Third, identifying the strategies that can be used to overcome these constraints. Fourth, knowing the toolbox that is available to participants in the policy-making process to help get their preferred strategies implemented. While our focus will primarily be on American political institutions, many of the ideas and topics discussed in the class apply broadly to other democratic systems of government.

Core Competency 2: Statistics

PSCI 107 Introduction to Data Science

Marc Trussler (MW 1:45 pm - 2:45 pm)

Understanding and interpreting large, quantitative data sets is increasingly central in political and social science. Whether one seeks to understand political communication, international trade, inter-group conflict, or other issues, the availability of large quantities of digital data has revolutionized the study of politics. Nonetheless, most data-related courses focus on statistical estimation, rather than on the related but distinctive problems of data acquisition, management and visualization--in a term, data science. This course addresses that imbalance by focusing squarely on data science. Leaving this course, students will be able to acquire, format, analyze, and visualize various types of political data using the statistical programming language R. This course is not a statistics class, but it will increase the capacity of students to thrive in future statistics classes. While no background in statistics or political science is required, students are expected to be generally familiar with contemporary computing environments (e.g. know how to use a computer) and have a willingness to learn a variety of data science tools. You are encouraged (but certainly not required) to register for both this course and PSCI 338 at the same time, as the courses cover distinct, but complimentary material.

Core Competency 3: Survey Research and Design

PSCI 207 Applied Data Science

John Lapinski, Stephen Pettigrew, Samantha Sangenito (MW 1:45 pm - 3:15 pm)

Jobs in data science are quickly proliferating throughout nearly every industry in the American economy. The purpose of this class is to build the statistics, programming, and qualitative skills that are required to excel in data science. The substantive focus of the class will largely be on topics related to politics and elections, although the technical skills can be applied to any subject matter. Prerequisite: PSCI 107 or PSCI 338.


PSCI 231 Race and Ethnic Politics

Daniel Gillion (TR 10:15 am - 11:15 am)

This course examines the role of race and ethnicity in the political discourse through a comparative survey of recent literature on the historical and contemporary political experiences of the four major minority groups (Blacks or African Americans, American Indians, Latinos or Hispanic Americans, and Asian Americans). A few of the key topics will include assimilation and acculturation seen in the Asian American community, understanding the political direction of Black America in a pre and post Civil Rights era, and assessing the emergence of Hispanics as the largest minority group and the political impact of this demographic change. Throughout the semester, the course will introduce students to significant minority legislation, political behavior, social movements, litigation/court rulings, media, and various forms of public opinion that have shaped the history of racial and ethnic minority relations in this country. Readings are drawn from books and articles written by contemporary political scientists.

PSCI 237 The American Presidency

Marie Gottschalk (TR 10:15 am - 11:45 am)

This course surveys the institutional development of the American presidency from the Constitutional convention through the current administration. It examines the politics of presidential leadership, and how the executive branch functions. An underlying theme of the course is the tensions between the presidency, leadership, and democracy.

PSCI 498 Administering Elections

Marc Meredith (T 1:45 pm - 4:45 pm)

Selected Topics in Political Science. More information will be posted shortly.

ECON 032 Political Economy

Deniz Selman (TR 12:00 pm - 1:30 pm)

This course examines the effects of strategic behavior on political outcomes and government policies. Topics and applications may include voting behavior, candidate competition, voting systems, social choice and welfare, policy divergence, redistributive policies and theories of political transitions. Credit will NOT be given for ECON 032 and ECON 232.

COMM 125 Introduction to Communication Behavior

Yphtach Lelkes (MW 10:15 am - 11:15 am)

This course introduces students to social science research regarding the influence of mediated communication on individual and collective attitudes, beliefs, and behaviors. Throughout the semester we explore the impacts of various types of mediated content (e.g., violence, gender and sexuality, race and ethnicity, politics and activism, health and wellbeing); genres (e.g., news, entertainment, educational, marketing); and mediums (e.g., television, film, social media) on what we think and how we act. The aim of the course is to provide students with (1) a general understanding of both the positive and negative effects of mediated communication on people's personal, professional, social, and civic lives; and (2) the basic conceptual tools needed to evaluate the assumptions, theories, methods, and empirical evidence supporting these presumed effects. Class meets twice a week (MW) as a lecture and once a week (F) in smaller discussion groups led by graduate teaching fellows. In addition to a midterm exam and occasional short assignments, students have the option of producing a multi-media capstone project or a final term paper on a media-effects topic of their choice. Group projects or final papers are permitted, with approval of the instructor. In addition to fulfilling General Education Curriculum Sector 1 Requirement (Society), this course fulfills one of the two introductory-level courses required of Communication majors or prospective majors.

COMM 210 Quantitative Research Methods in Communications

Matthew Brook O'Donnell (MW 12:00 pm - 1:30 pm)

This course is a general overview of the important components of social research. The goal of the course is to understand the logic behind social science research, be able to view research with a critical eye and to engage in the production of research. It will cover defining research problems, research design, assessing research quality, sampling, measurement, and causal inference. The statistical methods covered will include descriptive and inferential statistics, measures of association for categorical and continuous variables, inferences about means, and the basic language of data analysis. Course activities will include lectures, class exercises, reading published scientific articles, using statistical software, and discussing research featured in the news.

COMM 436 Data Literacy in the Algorithmic Society

Sandra Gonzalez-Bailon (TR 3:30 pm - 5:00 pm)

Algorithms regulate many areas of social life: they shape the information you see online, how resources are allocated, or how hiring and matching happen in private and public settings. In these and many other examples, algorithms rely on data informing the automated decisions they encode. Our ability to think critically about that data is, thus, paramount to understanding how the algorithms operate. In this course, we will discuss how data is transformed into information and actionable knowledge. You will learn how to question data to ensure their validity, reliability, and representativeness. Understanding how data are collected, analyzed, and used is key to being able to demand transparency in automated decision-making, and to exercising our democratic role of demanding accountability when decisions are made based on questionable data.