Big Data is a constant improvement for Higher education systems - and this is why

Big data nowadays has become present in almost every single aspect of our lives - from our navigation systems, to our healthcare and passing through our netflix recommendations. No wonder then, it will also be present in our studies. Higher education systems and universities nowadays have adopted the use of Big Data as a mutually beneficial tool that both increases profits and offer benefits for its clients (the students). The use of big data in education systems is far from conventional; the use of personality tests to adjust to different learning styles, using data to predict and recruit future athletic stars and assessing the likelihood of future dropouts using predictive analytics are just some of the benefits that Big Data can offer to universities. 

Universities begin to acknowledge that different learning styles originate from how differently different individuals see and interact with our surroundings. These differences shape how we respond and react to things (in this case a teachers’ classes, lectures, exams, etc.) and eventually affect both the quality and the quantity of the information we manage to obtain from our academic experiences. This said, big data enters the game in order to make better use of such valuable information obtained from personality tests on students. Universities store the observations acquired from these personality tests, along with other social indicators and performance of the students in databases, in order to then retrieve useful patterns about the necessities of students and create learning environments which improve the students’ learning experience. Apart from customizing academic plans for students, they can also be benefited by using information about their personalities to draw better plans for their future careers. For instance, it is logical to think that students who score high on perfectionism or have signs of obsessive-compulsive disorder might be more prone to choose a science career, whereas more creative and open minds are associated with social studies. Of course, this is a generalization and is not indicative at all but only suggestive, given that there are plenty of other factors involved.

It is no secret that universities with reputation attract more applications and students wishing to enroll in its program. Due to this, universities use big data trends in order to scout potentially successful athletes (a.k.a specific-program students), which eventually end up increasing the number of enrollments for the next academic year because logically a university with sport stars have a very good name or brand which results attractive for other students. Another way in which universities use big data in order to target specifics is by storing information about students who have applied (e.g high school GPA, test scores, demographics, etc.) and make predictions about the likelihood of success of those students. 

Increasing retention

    Universities have now started using big data by using predicting analytics to solve one of their main problems, college dropouts. By analyzing the possible students who might dropout, professors and advisors  can help them with specialized plans or degree changing before it is too late. Big data and predictive analytics can also help universities identify non-academic related reasons for dropouts, making administrators think of possible solutions or plans that adjust to specific problems, increasing the retention rate of students. 

In conclusion, it is clear how universities which use big data in a smart and efficient way can end up creating benefits for both themselves and their students. Moreover, the relationship between Big Data and Higher Education has very important implications for universities who have not still engaged in such data analysing activities or are not doing so successfully. Such colleges and universities should first manage to collect information from their students in an ethical and privacy-respecting manner, store that information in secure databases, and finally have trained employees in order to interpret and draw useful patterns from the data. A good managing of these aspects will offer universities benefits in various aspects like customizing learning plans, targeting specifics, increasing retention and many more. 

Bar Ben Avraham

Román Sanahuja