On Our Radar features HEQCO staff and guest bloggers offering their unique perspectives on trends, new ideas and hot-button issues in higher education. The opinions are those of the authors.
For years, postsecondary institutions have collected massive amounts of data but have not used them to their full capacity. Postsecondary institutions have a vested interest in improving student experiences, completion times and retention rates, and if they don’t, they should. While there are no clear solutions to these problems, data mining and academic analytics, which tend to draw on administrative and other relevant student data, are being used by some postsecondary institutions and appear to be a step in the right direction.
Applications that rely on data mining and analytics can be used by administrators, instructors, advisors, students and others. How can students who are registered and about to start their postsecondary program benefit from data mining and academic analytics? In my opinion, one of the best applications is the virtual advisor. Although similar to traditional advisors that guide students through their postsecondary experience, it’s not meant to replace them but more to assist them and the students.
For example, Arizona State University provides a wide array of services and supports through its eAdvisor, which tracks students’ progress during their first four semesters, helps plan course selection and alerts students and advisors if a student is not on track. Students deemed off track must see an advisor prior to registering for any additional courses. Should they remain off track for two consecutive semesters, they may be required to switch majors.
Purdue University’s Course Signals predicts student success in a course by combining information about their grades in the course, their time on task and past performance. Each participating course provides students with a colour based on these three elements. Green signals that students have a low risk for poor performance, yellow signals that students have room for improvement and red signals that students have a high risk for poor performance. Unlike eAdvisor, Course Signals is heavily dependent on the cooperation of course instructors as they decide how often to run signals in a course.
Although just scratching the surface of data mining and academic analytics for higher education, these are innovative approaches to the on-going institutional challenge of increasing student success. Some may be wary of the Big Brother aspects of applications such as eAdvisor, to which I would respond, show me something better that actually works.
While applications such as those at Arizona and Purdue are perhaps more invasive than a traditional advisor, they do create positive results. Increased student success including course grades and retention rates have been reported by multiple institutions. Innovation seems to be the buzzword of the day and while most of us just talk about it, the examples above show that some are actually doing it. We have far too many talkers in this sector and we should be embracing the doers. If there are problems with the techniques, let’s offer some solutions rather than just simply criticize. We need not look too far to see where that has gotten us.
– Lindsay DeClou, Research Analyst