Handbook of Learning Analytics

Chapter 20

An Introduction to Fairness, Absence of Bias, and Equity in Learning Analytics

Suraj Uttamchandani & Joshua Quick


In this chapter, we examine the ways educational justice has been and may be taken up in learning analytics research. To do so, we first outline how we see equity as playing a necessary role in the future development of the learning analytics community. Next, we review how equity has been explored in this area heretofore, focusing on notions of algorithmic fairness and absence of bias. Then, we turn to newer political approaches to the study of learning that are emerging in the learning sciences. We summarize trends in this research’s conceptualizations of equity and the political dimensions of learning. Finally, we connect these related ways of thinking about social justice with respect to learning analytics, and examine the tensions and possibilities at their intersection. We close with some recommendations for the learning analytics field to ensure that it contributes to positive educational change moving into the future.

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