Learning Analytics

Time-to-Adoption: Four to Five Years

Learning analytics promises to harness the power of advances in data mining, interpretation, and modeling to improve understandings of teaching and learning, and to tailor education to individual students more effectively. Still in its early stages, learning analytics responds to calls for accountability on campuses across the country and leverages the vast amount of data produced by students in day-to-day academic activities. While learning analytics has already been used in admissions and fund-raising efforts on several campuses, “academic analytics” is just beginning to take shape.

Learning analytics refers to the interpretation of a wide range of data produced by and gathered on behalf of students in order to assess academic progress, predict future performance, and spot potential issues. Data are collected from explicit student actions, such as completing assignments and taking exams, and from tacit actions, including online social interactions, extracurricular activities, posts on discussion forums, and other activities that are not directly assessed as part of the student’s educational progress. Analysis models that process and display the data assist faculty members and school personnel in interpretation. The goal of learning analytics is to enable teachers and schools to tailor educational opportunities to each student’s level of need and ability.

Relevance for Teaching, Learning, or Creative Inquiry

  • The promise of learning analytics is that when correctly applied and interpreted, they will enable teachers to more precisely identify student learning needs and tailor instruction appropriately.
  • If used effectively, learning analytics can help surface early signals that indicate a student is struggling, allowing teachers and schools to address issues quickly.

In Practice

For Further Reading

7 Things You Should Know About Analytics
(EDUCAUSE, April 2010.) This brief report explains how analytics are used for teaching, learning and assessing student progress.

Academic Analytics
(John P. Campbell and Diana G. Oblinger, Educause, October 2007.) This paper gives an overview of academic analytics and includes a guide to references and resources.

What are Learning Analytics?
(George Siemens, eLearnspace, 25 August 2010.) This article presents an overview of learning analytics and discusses how they might be applied in learning institutions.