Various types of structured data collected by learning management systems such as Moodle have been used to improve student learning outcomes. Learning analytics refers to an assortment of data analysis methods used for this task. These methods typically do not consider unstructured data such as blogs, discussions, e-mail, and course messages.…

Dartmouth and MIT have developed educational behavior apps and wearable devices that collect contiguous streams of data from student users. Given the consent of the user, the app collects information about a student's physical activity, sleep patterns, and location to form conjectures about social and academic behavior. These apps have the…

Data-informed instructional methods offer tremendous promise for increasing the effectiveness of teaching, learning, and schooling. Yet-to-be-developed data science approaches have the potential to dramatically advance instruction for every student and to enhance learning for people of all ages. Next steps that emerged from a recent National…

This article describes the crossroads between learning analytics and learner engagement. The authors do this by describing specific challenges of using analytics to support student engagement from three distinct perspectives: pedagogical considerations, technological issues, and interface design concerns. While engaging online learners presents a…

Learning technologies are now commonplace in education, and generate large volumes of educational data. Scholars have argued that analytics can and should be employed to optimize learning and learning environments. This article explores what is really meant by "analytics", describes the current best-known examples of institutional…