Subversive Learning Analytics
Award-winning paper that challenges the "assumptions" in Learning Analytics

LEARN doctoral student Juan Pablo Sarmiento, masters student Maurice Boothe Jr., and director Alyssa Wise presented their work at the International Conference on Learning Analytics and Knowledge (LAK) conceptualizing Subversive Learning Analytics (SLA). SLA arises from the premise that data should be used as a transformative force for change, rather than to perpetuate an often-problematic status quo, and uses a critical stance to reveal and challenge the power structures and inequities in education.

This paper won the best short paper award at LAK '21.

This paper puts forth the idea of a subversive stance on learning analytics as a theoretically-grounded means of engaging with issues of power and equity in education and the ways in which they interact with the usage of data on learning processes. The concept draws on efforts from fields such as socio-technical systems and critical race studies that have a long history of examining the role of data in issues of race, gender and class. To illustrate the value that such a stance offers the field of learning analytics, we provide examples of how taking a subversive perspective can help us to identify tacit assumptions-in-practice, ask generative questions about our design processes and consider new modes of creation to produce tools that operate differently in the world.

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