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Improving Student Graduation Rates Using Data Insights and Predictive Modeling
December 16, 2014 | A session at the EDUCAUSE LIVE! - Improving Student Graduation Rates Using Data Insights and Predictive Modeling

This session is a continuation of the conversation started at the EDUCAUSE Annual Conference in Orlando on innovative initiatives to improve student retention. As part of an overall plan to improve…

7 Ways to Use Tech to Improve College Student Success
October 31, 2014

Educational attainment, academic achievement, student persistence, learning and development, and college completion. The success of college students is getting more attention these days with risi…

Study of Students and Information Technology, 2014
October 30, 2014

For the 2014 student techology use study, ECAR also collaborated with 213 institutions to collect responses from 75,306 undergraduate students about their technology experiences. Key F…

2014 Student and Faculty Technology Research Studies
October 30, 2014

EDUCAUSE Technology Research in the Academic Community This research can catalyze conversations among IT professionals about how to better serve their constituents; among institutional leaders…

Automated Attendance Monitoring and Intervention for Student Success
March 18, 2014 | A session at the EDUCAUSE Connect: Chicago

Studies show that classroom attendance directly correlates to student success. Accordingly, the University of Mississippi has implemented an automated system to track attendance in lower-division…

Mobility, Connection, Support: Nudging Learners to Better Results
December 6, 2013

Key Takeaways This case study expands on early work that outlines how one college is nudging students to greater performance, engagement, and retention . Students received …

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…

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…

Progress Report: NGLC Learning Analytics Projects
September 23, 2013

Think of learning analytics as the warning lights of online learning’s dashboard – that gleaming assemblage of dials and icons that alerts a driver at once if gas in the tank is running low, …

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' …

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