Abstract This article considers the developing field of learning analytics and argues that to move from small-scale practice to broad scale applicability, there is a need to establish a contextual framework that helps teachers interpret the information that analytics provides. The article presents learning design as a form of documentation of pedagogical intent that can provide the context for making sense of diverse sets of analytic data. We investigate one example of learning design to explore how broad categories of analytics-which we call checkpoint and process analytics-can inform the interpretation of outcomes from a learning design and facilitate pedagogical action. Keywords learning analytics, learning design, pedagogical intent This article examines two relatively new concepts within education, learning analytics, that is, the collection, analysis, and reporting of data associated with student learning behavior, and learning design, that is, the documented design and sequencing of teaching practice, and how together these may serve to improve understanding and evaluation of teaching intent and learner activity. Learning analytics offers a passive method of gathering information on how learners are interacting with learning resources, each other, and their teachers. Unlike traditional surveys or focus groups, which rely on participants both opting to provide feedback and accurately remembering and reporting pas
