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Analytics for Teaching, Learning, and Student Success
July 25, 2012

Analytics: A 3 Day Sprint - July 25th, 2012 How does analytics affect faculty and students? Explore early warning systems, educational pathways, and use of student data to improve courses.…

Learning Analytics: Moving from Concept to Practice
July 19, 2012

This ELI Brief describes the evolution of learning analytics (LA) over the past year, drawing on two major recent conferences devoted to the theme of learning analytics: the ELI 2012 Spring F…

On "Trak": First Steps in Learning Analytics
July 18, 2012

Susan Tull is a Flexible Learning Advisor at the University of Canterbury. Key Takeaways A current focus at the University of Canterbury is to develop a cultu…

Navigating the Waters of Learning Analytics
July 24, 2012

Malcolm Brown, Director , and Veronica Diaz, Associate Director, EDUCAUSE Learning Initiative Navigating the waters of learning analytics (LA) requires steering a careful course between…

On the Horizon: The Power and Potential of Analytics
July 23, 2012

 “We are at the dawn of an era in which educators have the potential to harness technology to produce a dramatic change in student achievement.  Although visionaries have been promising for y…

From Data to Action: Driving Innovation through Predictive Analytics
September 10, 2013 | A session at the EDUCAUSE LIVE! - From Data to Action

Higher education institutions are increasingly looking to deliver and analyze data to drive results. Colleges and universities are working to increase student retention and assist students' …

Case Study 4: Yakima Valley Community College: Using Near-Real-Time Data to Increase Student Success
May 2, 2012

A case study from Game Changers Wilma Dulin, Sheila Delquadri, and Nicole M. Melander Overview In July 2006, Yakima Valley Community College (YVCC) joined the Achieving the Dream…

Chapter 4: From Metrics to Analytics, Reporting to Action: Analytics’ Role in Changing the Learning Environment
May 2, 2012

A chapter from Game Changers Linda Baer and John Campbell This chapter is licensed under a Creative Commons Attribution 3.0 Unported License What will the game-changing…

Who Are Your At-Risk Students? Using Data Mining to Target Intervention Efforts
October 16, 2013 | A session at the EDUCAUSE Annual Conference 2013

Improve targeted intervention by building a model to identify and classify at-risk students using data at your institution—and do it in-house with available data-mining tools. Find out how we did…

Predictive Analytics: A Case Study in Improving Student Success
October 16, 2013 | A session at the EDUCAUSE Annual Conference 2013

Learn how the University of Maryland University College is improving student success rates by leveraging predictive analytics to identify at-risk students and providing relevant interventions. UMUC…

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