the University of Alabama is a poster child to leverage big data in education and reap great benefits. With more than 38,000 students, the university has a sea of data, but in the past, Alabama’s data analysts had to manually pull information and transcribe them into spreadsheets. It was a tedious, time-consuming process that took weeks or even months.
Now with the help of big data analytics, they can pull data, analyze and produce reports in minutes. Administrators have at their fingertips all the information they need to make decisions and implement policies. They are able to quickly assess what-if situations and spot patterns with students. With the help of analytics and data visualization You have transformed the university’s efforts, recruitment and retention.
And Alabama is just one of many universities that use big data and analytics to accelerate innovative change:
- the University of Central Florida uses data visualization to create and meet the provost’s challenging 2020 goals.
- the University of Idaho uses analytics and data visualization to create a new, interactive way to share data with dozens of different components.
- the University of Louisville created a primary data platform to support the University’s strategic planning process in just 60 days.
A recent report from MIT Sloan Management Review, Analytics as a source of business innovation, validates this growing trend. For the first time in four years, survey results showed that a wider use of analytics and a greater focus on applications has resulted in the increased ability to use analytics for strategic innovation.
Big data in education: Transforming data into strategic insight
The report also showed an increase in efficient use of data. As you can see from Figure 1 below, the percentage of respondents who report that they can effectively use strategic insight data increased 6 percent. And there was a 3 percent increase in respondents reporting that they have access to useful data.
While the MIT Sloan Management Review study focused on business organizations, I am pleased to report that we are seeing similar gains in higher education as more and more institutions invest in data management, analysis and modernization of information delivery to policy makers. E.g:
- Sinclair Community College uses visual analysis to attract students, ensure gradual progression and completion.
- Des Moines Community College uses analytics and data visualization from SAS to access, integrate and manage data to help improve student enrollment, retention and graduation.
- Valencia College staff are able to explore data through interactive analytics visualizations wherever needed, accelerating data-driven decision making and reducing ad hoc report requests by more than 60 percent.
Big Data in Education: Analytics promotes many ways to innovate
The MIT Sloan Management Review report categorized respondents based on their level of analytical maturity. Analytical innovators, the most advanced category, “have an analytic culture, make data-driven decisions, and rely on analytics for insight and innovative ideas.” The next level, analytics practitioners, “has sufficient data access and is working to become more data-driven.” Analytically challenged are the least advanced organizations that rely more on intuition than data for decision making, and “they struggle with data access and quality and lack data management skills.”
While you expect analytic innovators to have an advantage over their less analytically oblique counterparts, you might be surprised at how wide the gap really is. As shown in Figure 2 below, analytic innovators are 60 percent more likely than analysts to use analytics for innovations in processes, products, and services.
In higher education University of Oklahoma is an excellent example of an analytical innovator doing just that. Instead of relying on intuition to predict which students will enroll and what actions recruiters need to take to attract them, the university solved the problem of big data and analytics.
Lisa Moore, an institutional research analyst at Oklahoma, used SAS® and two years of recording data to create four different predictable models using decision trees, logistic regression, forward stepwise regression, and backward stepwise regression. The project was completed in five weeks and the models were obtained Accuracy of 89-92 percent.
Moore provided decision trees for recruiting staff, and the visual aid helped them determine the most appropriate actions to take to entice students to choose Oklahoma. In fact, the recruitment director told her: “I did what you said and BAM! These kids signed up … it was a little creepy. “
Innovation with analytics resulted in the university’s largest and most academically prepared student body ever. It had more national merit students than any other public or private university. And Oklahoma doesn’t stop there – now it uses analytics for innovation in several areas, including selectivity, retention, and student satisfaction.
Big Data in Education: Sharing data helps organizations succeed
Another clear link between innovation and analysis is effective data sharing practices. The MIT Sloan Management Review report found that “organizations with a high ability to innovate share data both internally and outside of business boundaries at much higher levels than other companies: 80 percent of these organizations report sharing data internally, compared to 53 percent of others. organizations ”(see Figure 3 below).