UNLV Leverages Learning Analytics

October 18, 2016

The University of Nevada, Las Vegas (UNLV) is boosting student achievement and experience through learning analytics on the Splunk platform. Splunk is also helping the UNLV IT team prepare to host the final U.S. Presidential election debate on Wednesday, October 19th. Splunk will help ensure UNLV’s web properties and network infrastructure stay online during an expected spike in traffic during the debate, while also helping to proactively monitor and analyze the debate’s associated web and social media data. Learn more about how UNLV uses insights from Splunk by reading the case study and watching the video.

“We immediately made an impact across networking, datacenter and application support using Splunk Enterprise as our platform for machine data. Inspired by Splunk’s flexibility and impact out of the box, we quickly realized we could expand our use of Splunk into academic research too,” said Cam Johnson, manager of the Network Operations Center, UNLV. “Our research into how our students learn is helping us identify where and when student support is needed, enabling instructors to lead students toward academic success based on early indicators. Retention, progression and completion are very important to our mission and Splunk helps us meet these goals.”

UNLV is a rising national public research university serving 29,000 students. The university has used Splunk Enterprise for several years in IT operations to monitor the efficiency of its IT infrastructure and to help identify potential issues. UNLV’s Network Operations Center uses Splunk to ensure fast resolutions, system uptime and performance across the university for a more satisfying campus experience.

UNLV first used Splunk to analyze logs from its Learning Management System (LMS) for IT troubleshooting. With grant support from the National Science Foundation, the University then expanded its use of the platform into learning analytics research to improve how students learn. By mining and querying clickstream data from the LMS, UNLV researchers view which learning resources and studying behaviors most affect how well individual students perform. With this data, UNLV has developed the Early Warning and Learning Strategy Intervention program for instructors to identify students at risk of poor performance and to provide such students with customized learning materials to enable them to perform better.

In pilot programs, researchers collect data on students’ learning habits during the first four weeks of a course, and can then identify, with about 80 percent accuracy, any student who will eventually earn a C grade or lower in the course. Using this data as part of the intervention program, the instructor can then give the student specific feedback on how to improve. As a result, UNLV has seen better student success rates, with up to a third of students improving to A or B grades, and experienced lower class dropout rates.

“Predictive analytics can impact the world in untold ways, and UNLV is showing us the art of the possible. The University’s novel use of the Splunk platform to identify students who may underachieve is a solid example of the kind of change machine data can deliver to universities around the world,” said Kevin Davis, vice president of public sector, Splunk. “Educational institutions are analyzing data to provide better services to students, to keep critical IT services running, and to protect student data and the university infrastructure. Exciting developments like learning analytics only reinforce the need for the Splunk platform on campus to help better position students for success.”

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