Research Methods: Data Science, Justice, and Social Change
Mondays 2:10-4pm, Sch 200B; Wednesdays 2:10-4pm, Sch 200C
Essential course information
Welcome to the syllabus website for PSYC1495: Research Methods: Data Science, Justice, and Social Change. You can use the sidebar to access different syllabus sections, or the arrows on the sides of the page to scroll through the sections in order. Direct links to assignment sheets, rubrics, readings, etc. can all be found within the syllabus, as well as in the site Appendix. At the bottom of this page is a summary of the assignments for the current week.
If you prefer to read the syllabus in a good old-fashioned PDF, you can do so here.
Learning Objectives
- Students will learn the basic principles of designing a research study, including how to form questions and hypotheses, how to operationalize variables, how to determine experimental validity, how to identify sources of error, and how to interpret results.
- Using specific examples from criminal, gender, racial, and environmental justice, students will learn through “doing”: how to identify relevant administrative and other datasets; how to clean, integrate, analyze and learn from data; how to make and communicate the inferences and/or predictions; how to integrate close-to-the-problem expertise into problem solving; how to approach data and problem solving in ways that are consistent with justice values, where assumptions about data and statistical models are transparent; and how data can inform policy changes and bring about meaningful and just societal change.
- Students will learn how data may be misused in ways that perpetuate racial inequalities and biases, how policies that rely on gut-instinct and opinion can perpetuate injustice and structural racism (e.g., the policies that generated mass incarceration). Thus, students will learn to adopt a critical approach to data and policy formulation and to be vigilant for unintended consequences of well-intentioned efforts when data are used without an understanding of context and history.
Course Description
This course will provide the rigorous data science training and core content knowledge students need to use data science to effect policy changes that promote a more just society. We will explore these topics using readings, class discussions, guest speakers, and data analysis practice. The course will leverage the academic expertise of psychologists, lawyers, and data scientists; the perspectives and experiences of community members and students affiliated with the Center for Justice; and policymakers from government agencies and community organizations. The focus will be on collaborating with community and government organizations to propose data- and psychology-informed solutions that center on those most impacted by failures of the justice system. Students will learn how to promote a more just society through combining data, disciplinary knowledge, and fine-grained, on-the-ground experience. They will learn how to approach policy-relevant data with an explicit justice mindset such that they consider the implications of specific policies for achieving a more just, racially equitable outcome.
Role in the Psychology Curriculum
Students are increasingly interested in connecting academics with data-informed action. The work of the Center for Justice with communities and city and government agencies makes clear the value of educating students in how to use data to inform the transformation of law, policy and institutional practices. This course is an essential step in broadening our curricular offering to prepare undergraduates for the burgeoning interest in connecting psychology and neuroscience with public policy and law, and providing undergraduates the data science training they need to go on to graduate study, careers in public policy, etc.
This course is designed to give undergraduates an opportunity to learn about psychology research methods associated with data science research for social change. It is a research methods course with separate sections for lecture and lab. (Please be sure you are registered for both PSYC1495 and PSYC1496.) This is a 4-credit course.
- For the Psychology Major and the Postbac Certificate Program in Psychology, PSYC UN1495 can fulfill the Research Methods requirement.
- For the Neuroscience and Behavior Major, PSYC UN1495 can fulfill the P3 requirement.
Prerequisite: At least one previous psychology course AND an introductory statistics course. Please reach out to instructor if you do not meet these prerequisites but would like to take the course. Please note that previous coding or data science experience is NOT required to take this course.
What’s going on this week?
This section will be updated weekly.
- There is no reading quiz due on 11/3, as there is no class that day. However, there is still a reading for you to complete.
- Complete your lab assignment in Posit Cloud by the start of class on 11/5. We will have a guest speaker from NYC Open Data in class on 11/5
- As a reminder, you are only required to complete 8 reading quizzes and 8 lab assignments, but there are 9 of each. This means you can skip one or do an extra one for extra credit.
- Your final project outline is due by the end of the day on Wednesday, 11/12. See the final assignment page for instructions.