Research Practica
Research Practicum seminars will be offered every Fall and Spring Semester during the course of the project as 0-3 credit special topics courses (that can be retaken for credit). As an incoming trainee, you will start by enrolling in the Fall Research Practicum, where you will gain basic knowledge about current topics related to bias in data, humans, and institutions. The following Spring Semester you will conduct research with faculty and trainees from other disciplines, engage in collaboration, and present your work. These are expected to be collaborative and supportive settings, where trainees and faculty alike will have the opportunity to learn from one another.
Fellows (NRT-funded trainees) are required to participate in Research Practicum meetings for the entirety of their funding period (up to 2 years/4 semesters). Non-funded trainees are required to enroll in at least 2 seminars, but expected to remain active participants.
All new-incoming trainees must enroll in the Fall Research Practicum of their application year.
Fall 2026 Research Practicum
Course: PSY 610 - DETECTING & ADDRESSING BIAS 4
Class #: 92533
CMP/SCT: SEM S04
Days: Wednesdays
Time: 2:00-4:30 PM
Start_DT: 08/24/2026
End_DT: 12/17/2026
Bldg: Psych B
Room: 126
Instructor: Susan Bennan
Credits: 0-3
Trainees will learn to identify biases in the forms of data in their own and others’ research and methodology. They will conduct projects aimed at publication, exploring topics such as sampling bias, historical dataset bias in machine learning, bias in hypothesis testing, and the impact of biased data on automated decision-making.
Trainees will learn about anti-racism and practice techniques for identifying and addressing bias in themselves and in their own research. Topics may include: implicit bias, stereotyping and prejudice, heuristics that lead to biases in human judgments and decision-making, linguistic biases, and how to define, identify, and handle microaggressions.
Trainees will select several social/institutional domains in which to identify and document bias. Topics may include: structural racism, biased institutional practices, bias expressed in social networks, partisan conflict and disagreement in the media, and ways of remedying bias via education and policy.
