MSSP Resources

View a course grid for each iteration of the MSSP Program.

MSSP Core Courses

Students in the MSSP Program must take the following core coursework with an additional two elective courses for a total of 10 credit units (CUs). Students should follow the recommended course outline to ensure an on-time graduation. Any deviation requires approval of an academic advisor. All coursework is required. 

  • MSSP 6280: Policy: Analysis of Issues, Strategy and Process (1 CU)
  • MSSP 6290: Research & Evaluation Design (1 CU)
  • MSSP 6300: Quantitative Reasoning (1 CU)
  • MSSP 6310: Law and Social Policy (1 CU)
  • MSSP 8970: Applied Linear Modeling (1 CU)
  • MSSP 6680: Economics for Social Policy (1 CU)
  • MSSP 6320: Capstone I: Policy Communications (0.5 CU)
  • MSSP 6330: Capstone II: Policy Internship (0.5 CU)
  • MSSP xxxx: Theory Elective (1 CU)

MSSP+DA Core Courses

Students in the MSSP+DA Program must take the following core coursework with an additional two elective courses for a total of 12 credit units (CUs). Students should follow the recommended course outline to ensure an on-time graduation. Any deviation requires approval of an academic advisor. All coursework is required.

  • MSSP 6280: Policy: Analysis of Issues, Strategy & Process (1 CU)
  • MSSP 6290: Research & Evaluation Design (1 CU)
  • MSSP 6310: Law and Social Policy (1 CU)
  • MSSP 6680: Economics for Social Policy (1 CU)
  • MSSP 7100: Democratizing Data? Critical Data Studies in Algorithmic Governance (1 CU)
  • MSSP 8970: Applied Linear Modeling and Lab (1 CU)
  • MSSP 6070: Practical Data Science (1 CU)
  • MSSP 6080: Practical Machine Learning (1 CU)
  • MSSP/SWRK 7300: Community Mapping (1 CU)
  • MSSP 6340 Capstone I: Telling Stories with Data (0.5 CU)
  • MSSP 6350 Capstone II: Policy Internship in Data Analytics (0.5 CU)

Electives

Elective courses offer students the opportunity to maximize breadth in multiple substantive policy areas or to choose a specialized area of social policy analysis and conduct further research. Students in both the MSSP and MSSP+DA programs take two electives.

Elective courses taken outside of SP2 require an academic advisor’s approval. Students should submit the course name, course number, course description, and justification for taking the course to their academic advisor for review. Elective courses may be identified in any of the 12 graduate schools at Penn for possible approval and must be graduate-level courses (5000 or above) in order to count towards degree requirements. 

Use the MSSP Elective Course Guide to begin the process of choosing your elective coursework.

Theory Electives

The MSSP Theory Electives are intended to provide students with an understanding of how global forces such as capitalism, anti-Blackness, and settler colonialism influence policy formation and development. These courses also push students to wrestle with how to work through, with, and against policy to challenge global processes of oppression and build equitable, emancipatory, and justice-oriented worlds. MSSP Theory Electives examine these issues through the various frameworks of critical theory and through different assemblages of policy, governance, politics, and technology.

MSSP students are required to use one of their three electives to take an MSSP Theory Elective. Students choose from a menu of options offered by the MSSP program and may take the Theory Elective in the fall or spring semester. Courses that are considered MSSP Theory Electives are indicated in the course descriptions below.

Course Descriptions

MSSP 6000 – 6190

MSSP 6010: The Power of Partnerships Between Government, Nonprofits, and the Private Sector

Everything from the Affordable Care Act to the Mayor’s Rebuild Initiative here in Philadelphia could not be implemented by government without strong and vital partnerships with nonprofits and the private sector. These collaborations provide an opportunity to help people, impact and change policy, improve outcomes, and multiply the impact that nonprofit and private sector organizations can have. The course will help graduate (and advanced undergraduate) students not only understand the theory, policy, and practice of these collaborations but also learn how they actually happen. Students will also learn the characteristics of these three sectors, their roles and contributions, and competitive forces that are often at work in the collaborative process. Topics for discussion will include attitudes and expectations in the public sector, the ingredients of effective partnerships, and effective communication strategies with elected and appointed officials. The course will be conducted on a seminar basis. Graduate students are expected to take an active part in shaping the discussion. Students will be expected to rotate leadership for the class discussions and to supplement course materials with independent study of relevant magazine and newspaper articles. Course grades are assigned as follows: 20 percent for class participation, 15 percent for an in-class written exam, 30 percent for a group presentation and write up of a case study, and 35 percent for a final project. High quality written work and accurate citations is an expectation in all assignments.

Spring

1 CU

MSSP 6060: Data for Equitable Justice Lab

Data for Equitable Justice Lab is a research course that gives SP2 master’s students an opportunity to analyze some of today’s most important social issues through data and, with instructor support, create a product for audiences well beyond the classroom. With guidance from lab instructors, students develop a project – either individually or as part of a team – to examine a contemporary social policy issue through the use of data, or to examine a social justice issue that concerns data or digital technology. In these projects, students will produce an op-ed, blog post, podcast, academic article, short film, or other product of their choosing that creates or contributes to contemporary policy discourse. This course helps students produce a data-focused work product that they can build on during their Capstone seminar.

Fall

1 CU

MSSP 6070: Practical Data Science

This course familiarizes students with no prior programming experience with the core concepts of programming and the practice of software development for data-intensive applications in industry and government. After this course, students will be comfortable (1) writing code to save and load from files and spreadsheets into basic data structures like strings, lists, and maps; (2) manipulating data with code to perform tasks like generating aggregate statistics and filtering data into subsets; (3) effectively communicating findings from interactive, exploratory programming with others; and (4) working with technical teams, using best practices of software development when building line-of-business applications.

Fall

1 CU

MSSP 6080: Practical Machine Learning

This course prepares students with no background in machine learning or data science to use tools from those fields effectively in applied contexts. Using GUI-based software – or optionally, by programming with libraries – students will build skills including (1) feature representations of spreadsheet-based or text datasets; (2) training classification and regression models for prediction tasks; (3) evaluation of machine learning model accuracy and error analysis; and (4) reasoning about predictive models and making tradeoffs like bias vs. variance, granularity and annotation complexity in labeled training data, and the ethical application of predictive modeling to human-centered data.

Spring

1 CU

MSSP 6200 – 6590

MSSP 6280: Policy Analysis of Issues, Strategy and Process

Policy analysis requires an understanding of social problems/social issues and the processes by which policy is developed and implemented. Critical skills in many policy frameworks include: problem definition and analysis, review of relevant research, identification of possible actions, implementation and evaluation, and fiscal analysis. Competency in written and oral communication is also essential. To develop these and related skills, this course utilizes as a base a dynamic social problem analysis framework that addresses issues of equity, equality, and adequacy. It also examines multiple theoretical and analytical perspectives. Through the review of contemporary and historical social policy debates and provisions, selected case examples, and policy briefs, this course provides students with an understanding of the policy roles of the legislative and executive branches of government, including goal setting, policy rulemaking and enactment, allocation of resources, financing, regulation, and implementation. The policy process at state and local levels of government will also be addressed. The primary focus is on U.S. policy although global policies will be discussed when relevant.

Fall

1 CU

MSSP 6290: Research & Evaluation Design

Research and Evaluation Design introduces social research methods in the context of social policy and program evaluation. The course provides a conceptual and practical understanding in the design of experimental, quasi-experimental, and non-experimental research and in the application of quantitative and qualitative methods. Students learn about the application of the research process and skills in all phases of assessing a social policy and developing a social program, including needs assessment, implementation analysis, and evaluation of policy or program effectiveness. Students learn to be critical and informed consumers of research and to apply guidelines of research ethics in social policy settings.

Fall or Spring

1 CU

MSSP 6300: Quantitative Reasoning/Social Statistics

This course provides an introduction to statistical inference. We will learn the fundamental tools of data science and apply them to a wide range of social science and policy-oriented questions. The objective of the course is to develop two broad skill sets: (1) an understanding of the conceptual foundations for why we might manage or analyze data in one way versus another, and (2) learning the computing and programming tools (using R) to manage, visualize, and analyze data. The topics covered in the course include descriptive statistics, measure of association for categorical and continuous variables, introduction to t-tests, ANOVA and linear regression, research design (e.g., sampling, measurement, and causal inference), and the language of data analysis. Students will learn how to apply statistical tools to data sources, to design research studies, to test hypotheses, and to interpret the results of quantitative studies. The lecture focuses on the conceptual foundations of statistical inference; R programming instruction is covered in the weekly lab sections.

Fall

Also offered as SOCW 6300

1 CU

MSSP 6310: Law and Social Policy

This course introduces students to the basics of the American legal system, focusing on the interplay between litigation and social policy. Students will learn how law, and particularly case law, is made, how to read case law and evaluate precedent, legal reasoning and argument. This course will utilize various teaching methods including introduction to the “Socratic” lecturing method which is frequently utilized in the study of law. Students will also study the structure of court systems at both state and federal levels as well as the litigation process and the role of law and courts in shaping and addressing social policy issues. Students will also learn the basics of several areas of substantive law, with an eye toward consideration of how that law has been, and can be, used to effect social change.

Spring

1 CU

MSSP 6320: Capstone Seminar I: Policy Communications

The focus of the Capstone Seminar is three-fold: 1) to enhance student integration of the theory and practice of social policy analysis; 2) to enhance the student’s competencies in the written and oral communication processes and procedures necessary for the policy world; and 3) to ensure basic knowledge about federal budget processes, stakeholder roles, and inter-organizational collaboration. Registration restricted to majors only.

Spring

0.5 CU

MSSP 6330: Capstone II: Policy Internship

Capstone II consists of an intensive, multi-week policy internship that is selected through a consultative process involving the student, MSSP advisors, internship coordinator/advisor, and mentors/supervisors at potential sites. The internship provides an opportunity for the student to expand horizons beyond the academic. It serves as a medium to integrate classroom learning with experiences in policy making activity. Registration restricted to majors only.

Summer, Spring, and Fall

0.5 CU

MSSP 6340: Capstone I: Telling Stories with Data

The volume and complexity of data continues to increase in the world around us, including science, business, medicine, social media and everyday human activity. This course aims to expose students to visual representation methods and techniques that increase the understanding of complex data. Good visualizations not only present a visual interpretation of data, but do so by improving comprehension, communication, and decision making. In this course, students will learn about the fundamentals of perception, the theory of visualization, and good design practices for visualization. The course will also provide hands-on experience on the process of data communication, from initial data analysis, to identifying appropriate visualization techniques, to crafting informative visualizations.

Fall

0.5 CU

MSSP 6350: Capstone II: Policy Internship in Data Analytics

Capstone II consists of an intensive, multi-week internship that is selected through a consultative process involving the student, MSSP advisors, internship coordinator/advisor, and mentors/supervisors at potential sites. The internship provides an opportunity for the student to expand horizons beyond the academic. It serves as a medium to integrate classroom learning with experiences in policy making activity. Registration restricted to majors only.

Summer, Spring, and Fall

0.5 CU

MSSP 6600 – 7490

MSSP 6680: Economics for Social Policy

Economics allows us to determine the costs and benefits of social policies like cash benefits, unemployment insurance, health insurance, pensions, education, etc. Policies typically affect the behavior of agents like individuals, families, and firms, and we have to take these reactions into account when analyzing policy. Economics allows us to predict how policy is likely to affect behavior by understanding how the policy changes individuals’ decisions, and what collective outcomes these myriad individual decisions bring about. For example, a universal basic income allows individuals to sustain themselves and their families when they are not working. At the same time, such guaranteed income has the potential to discourage people from looking for a job. If enough people are discouraged from looking for a job, employment in the economy will decrease, leading to lower production and lower tax revenues for the government. Policy makers have to take these phenomena into account in order to design a good income support system.

Fall

Also offered as SOCW 6680

1 CU

MSSP 7060: Behavioral Economics and Social Policy Design

This course will introduce students to the field of behavioral economics and its application to designing social policies concerning health, education, childcare, voting, poverty, financial stability, legal and regulatory frameworks, among others. Behavioral economics extends the classical textbook theory of how the “rational” economic individual – often referred to as homo economicus – makes choices to include insights from psychology, biology, anthropology, sociology, and other fields in order to increase the explanatory power of economic theories. While classical economics is still a useful tool for any social scientist to possess, behavioral economics, in the words of one of the fields founding fathers, Richard Thaler (2015), “is more interesting and more fun than regular economics. It is the un-dismal science.”

Spring

1 CU

MSSP 7100: Democratizing Data? Critical Data Studies in Algorithmic Governance

MSSP Theory Elective

With the advent of digital technologies and the increasing power of computational analytics, the proliferation and ubiquity of data production has increased at exponential rates enabling new possibilities for social analysis. This course will examine the emergence of democratizing data – the movement to make government and other data more widely or publicly available and its potential enabling for democratic possibilities.

The types of data being made available, through various analytic systems, and the ways in which their accessibility and inaccessibility is contributing to reconfigured power relations, will be described. The paradigmatic tensions and shifts that have emerged in the debates on “Big Data,” such as deductive versus inductive reasoning and the challenges posed to statistical sampling theory, will be interrogated. The appropriation of machine learning and predictive analytic algorithms for social analysis will be critically explored. Issues related to the ethical and legal use of administrative data, particularly data related to patient, client, student, and taxpayer information will be considered, as well as from internet-based sources including social media. Potential solutions to data security challenges will be additionally considered. Methods for web-scraping of data, analysis of web traffic data, and the use of social networking data in the modeling of social phenomena and public opinion will be examined.

Students will learn how to make results accessible to non-technical audiences via data visualization tools, such as web-based data dashboards and web-based maps. These topics will be discussed for the analysis of health, education, and social policy as well as their implications for questions pertaining to race, gender, class, sexuality, dis/abilities, age, and youth culture. This course will develop students’ knowledge of computational and data analytics and its applications for social policy analysis.

Fall

1 CU

MSSP 7300: Community Mapping

Geographic space is important to family and community well-being, as we know. community Mapping introduces students to geographic information systems (GIS), computer software for making maps and analyzing spatial data. Students will learn how maps have been used in social welfare history as well as how GIS can be used for needs assessments, asset mapping, program evaluation, and program planning. The course builds on research skills developed in SWRK 6150. For the final project, students have an opportunity to apply their GIS skills to creating maps related to their field placement. The use of such maps may lead to both program and policy change in neighborhoods and communities.

Spring 1 CU

MSSP 7410: Gender & Social Policy

Gender and Social Policy develops an advanced understanding of social policies through the lens of gender – a socially constructed classification system based on ideals of femininity and masculinity, which are most commonly understood to be binary, mutually exclusive categories corresponding to sex (female and male). (Gender is) a concept that pervades all aspects of culture: structuring institutions, social identities, cultural practices, political positions, historical communities, and the shared human experience of embodiment*. The class provides students with the opportunity to explore how social policies respond (and contribute) to the needs and risks of different groups of people based on gender classifications. Rather than a survey of “gender” policy, students will be introduced to key feminist and trans concepts and frameworks that can be applied to any social issue and policy intervention. Policy examples may include reproduction, state violence, exclusionary/inclusive space, and national emergencies. The topics and specific readings may change based on the class’s interests and current events. Class assignments are designed to provide an opportunity to practice applying gender theory, as well as for each student to examine a policy issue of import to them through a gendered lens.

*Paraphrasing Garland-Thomson, 2002, “Integrating Disability, Transforming Feminist Theory”, NWSA Journal, 14(3): pg 4.

Spring

Also offered as SWRK 7410

1 CU

MSSP 7500 – 8970

MSSP 7550: International Social Policy & Practice: Perspectives from the Global South

This interdisciplinary course will introduce students to social policy and practice perspectives from outside the U.S. and especially from communities in the Global South. The course will familiarize them with global professions and help prepare them for overseas/cross-cultural practice. Through the course students will identify numerous strategies and skills professionals have used to collaboratively build interventions within human rights, social policy, social welfare, education, healthcare and sustainable development arenas.

Fall

Also offered as SWRK 7550

1 CU

MSSP 7680: Social Policy Through Literature

Fiction provides a lens to look at social issues and social policy through the rich and understandable lives of human beings, their challenges, and their triumphs in the holistic context of their worlds. Through appreciation of the human condition as portrayed in literature, students learn to frame issues more precisely and present arguments in compelling and convincing ways, thus enhancing the capabilities of social workers, social policymakers, and other agents to influence policy change.

Spring

Also offered as SWRK 7680

1 CU

MSSP 7960: Family Economic Mobility: Problems and Policies

The experiences and voices of mothers, fathers, children, employers, children’s teachers, human service workers, job training providers, policymakers and others in cities across America graphically show us the “real life” challenges to economic mobility facing today’s families and organizations. These voices particularly illustrate how economic, social, and cultural policies, practices, and beliefs intersect to perpetuate economic inequality for low-income and many middle-income working families alike. The labor market, welfare and workforce programs, public schools and government are some of the institutions implicated in this intersection. In the course we deconstruct concepts such as the “work ethic,” “family-friendly workplace,” and “good jobs” in terms of economic, racial and cultural inequalities and, more broadly, in terms of their meaning, aims and rhetoric. At base, this course examines occupational mobility in America within the broad framework of capitalism, democracy, race, ethnicity and gender. Students from GSE, SAS, City Planning, and Communications often join SP2 students to read and critique classic and contemporary literature from multiple disciplines and explore generative roles for “meso-oriented” social change professionals.

Fall

Also offered as SWRK 7960

1 CU

MSSP 7980: Social Policy Topics: Reproductive Justice Policy

With the impactful decision of Dobbs v. Jackson Women’s Health Organization, the US Supreme Court in 2022 struck down almost 50 years of federal policy precedent of Roe v. Wade (1973). This opened a time of confusion as states scrambled to determine the meaning and implications of existing and future state and local policies. This course specifically utilizes the term reproductive justice. As Ross & Solinger (2017) describe, the definition of reproductive justice intentionally moves beyond the pro-choice/pro-life perspectives of policies regulating abortion and focuses policy assessment through core principles of 1) the right not to have a child, 2) the right to have a child, 3) the right to parent children in a safe and healthy environment, and 4) sexual autonomy and gender freedom for every human being. This course will first provide historical context of reproductive justice policy in USA history, then focus on local, state, and federal policies regulating reproductive justice. Policies will be particularly analyzed through the lenses of LGBTQ+, race, disability, and critical theory. MSSP Theory Elective. MSW Policy Option. Enrollment is limited to students with a major in Social Policy and Social Policy & Data Analytics.

Spring and Fall

1 CU

MSSP 7980: Social Policy Topics: Qualitative Methods in Policy Research

During a policy intervention, how can we learn from the lived experience of program participants, patients, and the community? Are their lived experiences able to generate innovative and alternative policy solutions? These are some of the questions that strategies of qualitative inquiry can address.

Qualitative inquiry provides much needed nuance and complexity that complements quantitative data, enhancing our understanding of social problems, and identification of people-centered solutions. Qualitative methods can empower individuals and communities and act as a conduit for their voices. For example, why do Black patients who have Black physicians report better outcomes? How do the lived experiences of people experiencing poverty establish different needs and solutions for achieving economic stability?

This course introduces students to a range of qualitative approaches that can yield insights for use in policy development and analysis. Students will learn how to conceptualize qualitative research questions, select appropriate methods, and develop skills through doing. Course topics include: research ethics, field observation, semi-structured interviewing, focus groups, coding, and analysis. Students who are currently developing their own research projects are encouraged to use this course to refine their methodological framework. Course does not fulfill MSW Policy requirement.

Spring

1 CU

MSSP 7980: Social Policy Topics: Global Abolition, Decolonization, & Social Policy

Social policy reflects social structure, and this course seeks to chart how dramatic transformations of that structure can give rise to previously unforeseen policy alternatives. Focusing on abolitionist movements past and present and ongoing global struggles for decolonization, we will analyze not only the concrete impact that these structural shifts produced in the realm of policy, but also—more qualitatively—what kinds of abolitionist and decolonized social policy alternatives can become possible in the process of dismantling entrenched structures of global inequality. MSSP Theory Elective. Course does not fulfill MSW Policy requirement.

Spring and Fall

1 CU

MSSP 7990: Independent Study

Independent studies provide a flexible opportunity for standing faculty and students to work together in pursuing a topic of special interest that is not sufficiently covered by other courses in the curriculum. The content of independent studies is highly specialized and, as such, requires a plan of study developed jointly by the student(s) and the supervising standing faculty member. Part-time faculty members are not eligible to offer independent studies. Independent studies require the academic advisor’s approval.

1 CU

MSSP 8970: Applied Linear Modeling

This course deals with how to critically and responsibly model real-world data to answer social science, education, and social policy-related questions, using the framework of the general linear model. Linear modeling (which, in statistics, is synonymous with regression analysis) is the workhorse of much of quantitative social science and, despite its enormous flaws and powerful limitations (which this course will also cover!), it remains an important tool to understand and be able to use.

The course builds up multiple regression from correlation and bi-variate regression, and then covers categorical independent variables, nonlinear transformations and polynomial terms, diagnostic checks, model-building and model iteration, interaction effects, mediation analysis, and logistic regression. Mathematical (e.g., Gauss-Markov) assumptions are covered but the emphasis is on deeper epistemic assumptions and more immediate practical limitations. While not covered in detail, pointers will be given to techniques for specific types of data (especially multilevel modeling for nested data) and to important modern developments (especially structural causal modeling, non-parametrics, and machine learning).

Throughout, the course will return to and emphasize critiques of linear modeling, to encourage students to be able to use (or choose not to use and oppose) regression analysis rigorously, critically, and responsibly. The course will be taught using R. Pre-requisite: MSSP 6300 Quantitative Reasoning/Social Statistics, or another Introductory Graduate Statistics course. The course will include an introduction to R, so a background in R or in programming is not strictly necessary, but it is helpful.

Spring and Fall

Also offered as SOCW 8970

1 CU