Which learning analytics (LA) approach might be the best choice for your teaching and learning context? Learning analytics as a field of research and application seeks to collect, analyze, report, and interpret educational data with the goal of improving teaching and learning. But hasty adoption of learning analytics tools and methods that are simply convenient, promoted or available risks allowing learning analytics to 'drive the pedagogical bus'. In this paper, we propose that careful reflection on pedagogical design choices and the learning theory that underpins them can and should inform selection of relevant learning analytics tools and approaches. We broadly review established learning theories and the implications of each for pedagogical design; for each design approach we offer examples of learning analytics most clearly aligned with the theoretical perspectives on learning and knowledge that have shaped it. Moreover, we argue that careful consideration of the learning theory underpinning the pragmatics of pedagogical design choices should guide LA implementation, and help educators and designers avoid the risk of gathering data on, and measuring outcomes for, activities that are not relevant to their pedagogical design or goals.