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The Truth About Student Success - Applying Student Data

The Student Success Movement

Educators have always wanted students to do well, but only in recent years has the responsibility for student success shifted from being placed solely on the student to being shared equally by academic institutions. Historically, graduation rates in the U.S. have been pitifully low, and at their highest point have still not yet reached 60%. Most institutions are led to raise retention rates due to financial needs, but in an era of increasing diversification in higher education the moral responsibility to close the gaps in success that minorities face adds to the need for institutions to take action. 

This pressing need to increase retention rates often has the adverse side effect of a fixation on solutions and quick fixes, instead of a long term planning and re-examining core processes. Programs or tools are helpful, but often fall short of their intended need. Even if these programs and tools fully realize their goal, grants run out and program managers move on. Deep systematic change, brought about by thoughtful and intensive review of all processes, is what is necessary for lasting and impactful improvements to student success.

An organization that is focused on the students, as opposed to ranking or research, is an organization that will put the students and their successes first.  

This Learn Twice article is one part of a four part summary of the paper "The Truth About Student Success: Myths, Realities, and 30 Practices That Are Working" from The Chronicle of Higher Education. The full paper requires purchase to view. The link to purchase the paper can be found in the right sidebar. Read our other three summaries of this paper for free here:

The Truth About Student Success - Improving the Educational Experience
The Truth About Student Success - Integrating Academic Support
The Truth About Student Success - Promoting Students' Well-being

Applying Student Data

Predictive Analytics is the practice of using various data points such as student background, academic performance, and student behaviour to identify both broad patterns and individual needs that can then be addressed. When these and other factors are used to determine at risk students, outreach programs and procedural changes can be put in place to help students succeed. Some schools have found success in applying the following principles and practices once a system of predictive analytics is in place:
  • Constant adjustments to analytics tools and to the application of various programs and procedures to help at risk students - The University of North Carolina at Greensboro has found success in adding less intuitive data points to their analysis such as how many miles a student lives from home, based on the assumption that some students may suffer from homesickness.
  • Coordination of advising efforts -  Some schools have centralized their advising departments with the intent of cross training advisors. This allows for students to be able to go to one place for all of the information they need instead of being sent all over campus to find answers to questions. Another tactic is to build extended outreach programs that include professors and mentors in addition to advisors. 
  • The case management method - Similar to visiting a doctor who has access to your medical history, when students at the University of South Florida visit with an advisor, all of their past information such as last weeks visit to the financial aid office or notes about their last academic advising visit, is available to the advisor. This allows for greater customization and personalization of advice and help. 

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