TAs work with student data all the time: grades, participation records, Quercus analytics, midterm feedback, and course evaluation comments. These data often inform how TAs grade, who they reach out to, and how they adjust tutorials, labs, or office hours. Yet the ways this information is collected, represented, and interpreted are never neutral. This workshop starts from the premise that data, like teaching, are shaped by values, context, and power. Building data literacy through an equity lens is therefore essential for ethical, inclusive, and transparent TA practice.
In this session, TAs will explore practical strategies for making their data-related decisions more equitable and accountable: from how they track participation and apply rubrics to how they interpret “engagement” and communicate feedback to students and instructors. Through discussion, case studies, and hands-on redesign activities, participants will identify biased data practices (e.g., participation policies, grading norms, analytics dashboards) and reframe them using frameworks such as Universal Design for Learning (UDL), Design Justice, and anti-oppressive pedagogy. By the end of the workshop, TAs will be better equipped to critically assess the data they use, interpret student performance with greater transparency and care, and apply inclusive design principles so that their teaching, supervision, and feedback practices support equity, trust, and student success.