7. Analytics technology becomes a key part of campus decision making.
For years, marketers have used sophisticated software to track consumers’ buying habits and web browsing activity, then crunch this information and—based on the data—make a series of intelligent predictions that allow them to target their sales messages much more effectively. Now, this same technology is appearing in schools and colleges as well—and observers say it’s a development that could revolutionize education.
Using predictive analytics software, Kennesaw State University in Georgia has been able to hone in on prospective students more efficiently. Sinclaire Community College in Ohio has cut its student dropout rate in half. And the online American Public University System has seen its course completion rate steadily climb.
These breakthroughs come at a key time for U.S. higher education, which is under enormous pressure to innovate and provide better learning opportunities.
Predictive analytics encompasses a variety of statistical techniques for mining information gathered across a variety of sources—for example, student information systems, library automation systems, learning management systems, and back-office enterprise systems—and analyzing those current and historical data to make predictions about the future.
The implications of predictive analytics for education are nearly endless. For instance, schools are using analytics software from companies such as IBM or SAS to track student performance over time, looking at various data points—not just test or quiz scores, but other, more subtle signals as well, such as how frequently students are logging on to a learning management system, or how often they’ve contributed to online discussions—to identify those who are at risk of failing or dropping out. Some schools are overlaying a system that can identify these early warning signs automatically and create a customized intervention plan for students who might need it.
Other colleges and universities are using analytics software to more accurately predict enrollment numbers, which helps them plan in a variety of areas—from budgeting and staffing to anticipating the amount of parking that will be available to students. Still other campuses are using predictive analytics to recruit students who are more likely to enroll and do well.
IBM has worked with industry leaders for years, helping businesses use predictive analytics for managing risk and improving their return on investment. Now, IBM has developed what it is calling a “vision for smarter education,” creating an analytics framework that combines predictive analytics with “intervention management” technology, which can trigger a specific intervention that is unique to each struggling student’s needs and deliver this remedial content directly to the student. The solution is in beta-testing now and will be commercially available for schools and colleges in early 2012.
The higher-education technology group EDUCAUSE, meanwhile, has launched a new initiative to encourage the use of analytics technology among colleges and universities. The project will culminate with a national summit for campus leaders to explore analytics use in more detail next fall.
Predictive analytics helped an IBM computer dubbed “Watson” beat two former Jeopardy! champions earlier this year in a highly publicized contest that showed how far artificial intelligence has come. After that demonstration, the Columbia University Medical Center and the University of Maryland School of Medicine signed on to test Watson’s capabilities to help doctors diagnose diseases more effectively.
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