7 Ways Universities Benefit From the Use of Data Analytics
When people hear the words data analytics, the first thing that comes to mind is conclusions. It leads them to ask questions like, “where will these findings take us?” or “how does it improve our conditions?” That last one is vital for institutions like universities. After all, it is a place that molds the futures of many people. With the right kinds of information at their disposal, planning becomes easier and platforms like social media are worth more than ever before. With that said, below are eight important benefits that await universities that open themselves to the possibility of improvement via data analytics.
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7 Ways Universities Benefit From the Use of Data Analytics
Improved Learning Experiences
Learning is a lifelong process that isn’t limited to university students. As they progress through their teaching careers, professors continue absorbing lessons as well. For both groups to achieve their greatest potential, universities must foster the right environment that’s most conducive for learning. Data analytics is useful in bringing this about, although the specifics will vary from school to school.
For example, a university can use predictive tools to determine that majority of the students make better progress with adaptive learning techniques. The results of those findings will not only enable students to have a better learning experience, but it also helps teachers when it comes to honing their teaching methodologies.
Better Decision Making
Providing a better overall environment for students and teachers alike is not easy. Pulling that off requires university administrators to make effective decisions over a wide range of areas. The complexities involved makes it easy to turn to data analytics for help. Prime examples include how to handle “at-risk” students and whom to target for scholarships.
Both circumstances are delicate and if done wrong, it may lead to disaster for everybody involved. In these examples, sound decisions equate to proper identification of who are “at-risk” and who deserve scholarships the most, which is where analytics come into play. The data a university can gather will help single out students for either category long before classes even start.
If there’s one definitive indication of a university’s improved status, it would be the rise of better-performing students. Yet this is not something that lies in the hands of the students alone. Performance management is an important responsibility for the administration and faculty as well. For better application, data analytics can provide answers on how to do this properly.
One way is to use analytics to help evaluate the current curriculum. There are times when specific courses experience greater-than-usual dropout rates. When administrators are informed about instances like this in a timely manner, they can make necessary adjustments to those courses, which in turn, will help students with their performances.
Lowered Retention Rates
If better student performance is an indicator of success, then surely an increase in retention is an indicator of the exact opposite. Nobody wants to see students remain in their present academic levels far more than necessary. It is not only a waste of time for both students and teachers, but it is an immense waste of money. More than once, at-risk students have been mentioned in this article.
Besides the aforementioned identification of who they are and how to improve their performances, there are other methods universities can employ to improve their retention through data analytics. Data can be collected on their class attendance, for example. That will lead to greater chances of successful supervision, which will lead to higher odds of academic success for them.
Better Recruitment Efforts
Scholastic recruitment is something that involves both the student body and the faculty. With the right equations in place, a university can determine if those they are recruiting—to study or teach—are worth the investment. As an example, let’s consider situations involving prospective enrollees. Those who attend classes and perform consistently well are the ones considered to be the best kind of students to recruit.
Finding them often involves weighing in various demographics, a multitude of academic history, along with factors like whether or not they are incoming freshmen, new transfers, and so on. With the use of data analytics, universities can commit fewer recruitment and admission mistakes. With fewer mistakes, they can maximize their efforts and receive the highest return on investment possible.
Easier Tracking and Data Access
On the technical side of things, a great benefit to data analytics is that it helps universities keep track of their data. Even without analytics, most universities today no longer keep physical files in bulky folders. Everything is digitized now. With that said, data analytics can help make sense of what’s being stored.
If the university wants to stay on top of how many new enrollees there are for a certain school year, then coming up with answers is faster than ever. Should there be a need to make reports on how certain departments are doing, then that’s now easier to do as well. Anything on your administrative checklist becomes much smoother to mark off when take advantage of the convenience presented by data analytics.
Greater Brand Recognition
When you put everything on this list together, there is another benefit that you can reap. That benefit is an improved reputation and branding for the university. Success stories travel fast and most are definitely interesting in learning where notable individuals got their start. Not only will greater brand recognition lead to an increase in enrollees, but it also creates an intangible mystique that’s difficult to intentionally recreate. Lastly, there is the loyalty that high performing universities gain. It is something expressed by both students and faculty, which is another irreplaceable perk caused one way or another by data analytics.
Any university that pays close attention to the results of their data analytics will improve by leaps and bounds. As you can see, the individual benefits are astounding. Even if the acquisition of these results won’t happen overnight, their eventual arrival remains an enticing thought. By starting with data analytics today, universities pave the road to a brighter tomorrow for everybody. Students, faculty, and administrators alike will reap these great rewards one day and there won’t be a tinge of regret when it happens.