When we talk about learning analytics in higher education, we have a tendency to focus on the negative. We talk about identifying at-risk students. We talk about discovering barriers to student success. We talk about reducing institutional inefficiency.

But analytics can also help institutions discover, scale, and optimize practices that are already working incredibly well.

Recently, while implementing X-Ray Learning Analytics at University College of Estate Management (UCEM), a data science team led by Blackboard’s Dr. Aleksander Dietrichson worked with UCEM’s Dr. Gethin Edwards and Dr. Peter Stone to determine whether activity patterns in Moodle differed significantly as a function of class size. Based on existing literature, one might expect to see engagement suffer in large enrollment online courses.

What they found was surprising.

In April 2014, UCEM established a tutoring program in order to increase consistency in course quality and student experience. What Blackboard’s research team discovered was that by assigning dedicated tutors to groups of 40–50 students in every large enrollment class, UCEM had virtually eliminated significant differences in student online activity patterns as a function of class size.

With strong evidence in support of the impact of their tutoring program, UCEM is now using analytics as part of a feedback cycle of continual improvement. Having used analytics to discover a high-impact practice, UCEM is now working to improve upon their success by providing rich analytics to tutors while adopting a data-driven approach to curricular development.

Download the full case study to learn more about how UCEM is using analytics and an effective tutoring strategy to drive student success. To learn more about how X-Ray Learning Analytics can support your student success efforts, please visit our product web page or contact us to schedule a demo.

Download our case study: Using learning analytics to understand student success in large enrollment courses

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