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Subversive Analytics

One of the critiques of learning analytics is that it can contribute (intentionally or otherwise) to perpetuating historical patterns of inequality. This new stream of work, initiated to help address systemic racism in education, seeks to upend that relationship by unpacking the assumptions that commonly underlie learning analytics solutions and exploring how they can be used as a tool for equity and social justice.

Illustration of three people pointing to network design

Student In-Sight

Learning Analytics can heighten power imbalances between students and faculty by creating asymmetrical visibility, where students’ academic and demographic data is shared with faculty, while students themselves are unaware of what is shared and to whom. The information shared, moreover, can paint a limited and reductionistic picture of students who have no opportunity to provide context for the information. This is particularly problematic in the context of historical patterns of inequality in educational access and opportunity. This project innovates new designs to address this challenge by fostering transparency in information sharing and allowing students to annotate their data. The aim is to generate a tool that encourages different members of educational communities (students, teachers etc.) to share perspectives that foster better understanding of the contexts and identities that are meaningful to each other.

Imagined Tools for Thinking

This project works with diverse stakeholders to create and compile sketches of imagined analytics tools that problematize aspects of the current status quo such as issues of misrepresentation, underrepresentation, and non-representation (missing but relevant data), as well as concerns about privacy, transparency, power and bias. These sketches can serve to inspire LA designers and constitute “objects to think with” for the mindful and critical use of LA.