Learning Analytics is the term academic technologists use for using student data to help with teaching and learning.  Some schools have started collecting student information from a variety of sources and using it to alert faculty about potential problems.  The data can come from learning management system activity (Moodle), clicker responses, online homework results, admissions data (grades, test scores, etc), transcript data (related courses, grades), or class and help session attendance.

For example, a first year student student with lower-than-average high school GPA and SAT scores that hasn’t logged into Moodle for 2 weeks and is late submitting an assignment, might benefit from a discussion with his or her professor before an exam.

EDUCAUSE, the higher-education information technology organization, has put out a two page summary  called 7 Things You Should Know About Developments in Learning Analytics, which is a quick read if you’d like to learn more about the topic.

At big schools, much of the focus for these types of tools has been on student retention.  At Swarthmore, where student retention is high, we’ve discussed if there are other areas that could benefit from analysis of student data.  Our conclusion has been that smaller class sizes, the “big brother” aspects of these projects, and the complexity of the required software means that learning analytics isn’t a good fit for Swarthmore.  If you think there might be possible applications for your classes or department, we’d be interested to talk with you.  Get in touch with your Academic Technologist with your ideas or questions.