From a Nominal to Normative Commitment: Liberating Learning Analytics from Embedded Biases Through a Sociotechnical Systems Approach

Abstract

The emphasis on "Can we do this thing with these data?" detracts from other important goals of learning analytics (LA) beyond understanding and optimizing student learning. It also undermines LA's ability to develop a coherent epistemology and be consistent with its stated values of openness, fairness, and justice, equity, diversity, and inclusion (JEDI). Acomprehensive theoretical framework accounting for LAs' macro, meso, and micro level domains would enable more epistemologically cohesive, sociotechnical system approaches ot be taken, which could help shift nominal commitment to values to a normative one.