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Predictive analytics, basically follows a wide range of statistical methods from predictive modeling, machine learning, artificial intelligence and data mining that evaluate and analyze the facts from the present as well as the past to make predictions about future or any unknown events. Predictive analytics is used in Customer relationship management (CRM), healthcare, cross selling, fraud detection, risk management, direct marketing, underwriting, etc.
In the field of education, the desire for stronger actions and efficient operations is leading colleges and universities to alter their methods of operation. Universities have started facing increasing pressure to beat the inflation on tuition fees, the burden of student cumulative debt money, outstanding credit card debt that is to be collected and rejection of state funds. These situations demand well-organized business practices to be more efficient in the competitive market.
Since the online systems like Learning Management System and Student Information System are the driving functions in educational institutes, a colossal amount of data about students, workers, sponsors, and graduates get stored during each and every transaction that is being done. This series of online analysis applications goes beyond reporting and monitoring. This data can further be used in analysis and estimation of the future. Institutes today make decisions based on these estimation results that are produced based on events already occurred. Later the actuals are compared with the estimated results to see if the improvement exists as expected. The common areas of improvement are
Predictive analysis provides perceptions on events even before it occurs. Hence the outcome of the event can be influenced. For example, Google map uses GPS and location information about our current location and destinations and suggests the best possible route and all possible alternate routes to reach the destination safer and faster. In a similar way, the data of the student is used to analyze the factors that can affect the student from reaching the goals and deadlines. The progress of the student is estimated at the initial point itself. Any hurdle that may cross the way can be arbitrated and eradicated in a proactive manner so as to helps the students attain the goals with ease. This whole process seems tedious and tough, but is helpful.
The reason why any educational institute should go for predictive analysis depends and varies from institute to institute. But the common expectation is to have a foreseen vision at each and every step of this entire process. Hence the path to be taken is known and understood beforehand and it helps in meeting the objectives of this entire process. The end results are very efficient and powerful in terms of students and faculty management.
Mostly the institutes that provide higher education widely uses the predictive analysis. Their primary motto is to make the feel and experience of the students during their tenure in the institute better. Predictive analysis is also used by the educational institutes to attract students around the globe, retain students, offer personalized education and also support different monetary decisions. This in turn benefits the institute, faculty, students as well as the parents.
Where to Focus?
There are multiple areas where predictive analysis can focus. It depends on the objective and the business of use. Usually, at educational institutions, the primary area of focus will be staffing, enrollment, retention and personalized education. These are the common areas where the usage of predictive analysis improves outcome.
Some institutes are apprehensive of taking the longer route and are keener in testing the waters first, to get a feel of it. Most customers have started to try out predictive analysis solutions which doesn’t need any monetary investment.
This is the right time for all the educational institutions to start using the predictive analysis as it helps to provide the best to the students, faculty, parents as well as the institute, by analyzing the data available and predicting to help shape a fine future.