Centering Student Voice in Developing Learning Analytics and Artificial Intelligence–Embedded Supports

Abstract

Accelerating advancements in learning analytics and artificial intelligence (AI) offers unprecedented opportunities for improving educational experiences. Without including students’ perspectives, however, there is a potential for these advancements to inadvertently marginalize or harm the very individuals these technologies aim to support. This article underscores the risks associated with sidelining student voices in decision-making processes related to their data usage. By grounding data use within a social justice framework, we advocate for a more equitable and holistic approach. Drawing on previous research as well as insights we have gathered from a student panel, we outline effective methods to integrate student voices. We conclude by emphasizing the long-term implications for the institutional research field, arguing for a shift toward more inclusive and student-centric practices in the realm of learning analytics and AI-embedded supports.