The use of “big data” in business is widely known and mostly accepted by both businesses and consumers. (Think of Amazon’s ability to suggest products you may like based on previous purchases or views.) However, its use within colleges and universities has been halting and sporadic. Big data is growing in both popularity and acceptance as institutions work to find new and innovative ways to enhance the student experience and increase student success. A growing number of colleges and universities are using analytics at the level of the individual learner to support and target instructional, curricular, and/or support resources and interventions. In the higher education field, “analytics” is usually referred to as “learning analytics” (LA) or “academic analytics” (AA).
The annotated bibliography linked below was originally produced by Lauren Hirsh, a DELTA graduate student, in 2013. DELTA’s Coordinator for Learning Analytics and Assessment Chris Willis, updated the document in March 2017 to include recent trends in the literature that help put the current state of LA into context for experts and novices alike. These trends focus on (1) defining the field for academic institutions; (2) ethics and privacy concerns in LA; (3) creating, improving and/or evaluating LA theoretical constructs; and (4) improving LA output and application. This annotated bibliography provides some resources for consideration and further exploration of learning analytics in higher education. While it is not a comprehensive review of the literature, lists of additional articles and further resources have been included at the end of the document.