Introduction

Abstract

Learning analytics encompasses a range of cutting-edge educational technologies, methods, models, techniques, algorithms, and best practices that provide all members of an educational community with a window into what actually takes place over the trajectory of a student’s learning. This chapter provides an introduction to the volume more generally, which attempts to provide an entry point into the field by showcasing the latest results, strategies, guidelines, methods, models, and tools. Collecting all of this information in one volume will allow researchers, instructors, educational administrators, and others interested in learning analytics to take stock of ongoing efforts in the field depending upon their unique institutional interests. As a field with a broad appeal, simply navigating the extant literature of learning analytics, let alone attempting to put any of those principles into practice, can prove daunting. The volume’s chapters each attempt to consolidate much of the available literature while putting forth best practice guidelines or model case studies that might prove of interest to particular types of readers. As such, this book is organized not around common problems or the mounting complexity of its efforts, but rather around the kinds of communities that each chapter attempts to address.