Higher education data mining and analytics, like learning analytics, may improve learning experiences and outcomes. However, such practices are rife with student privacy concerns and other ethics issues. It is crucial that student privacy expectations and preferences are considered in the design of educational data analytics. This study forefronts…

This chapter reviews actionable data use--both as an umbrella term and as a specific concept--developed in three different traditions that data/information can inform and guide P-20 educational practice toward better outcomes. The literatures reviewed are known as data-driven decision making (DDDM), education data mining (EDM), and learning…