Student Sensemaking of Learning Analytics Dashboard Interventions in Higher Education

Abstract

An instrumental case study was conducted at a large, public research university in the mid-Atlantic region of the United States to understand undergraduate use of learning analytics dashboard (LAD) interventions. Eighty-one undergraduate students participated in focus groups. Scenario-based questions, modeled on current and future LAD interventions, were asked to understand student uses, perceptions, and reactions to these interfaces. Results indicate that student sensemaking is tied to data relevance, accuracy, and context. Further, trust in both data, especially predictive data, and in relationships, especially with faculty, are foundational to the sensemaking of LAD data and interventions. A model of student sensemaking of LAD interventions is provided.