How Predictive Analytics is Transforming Higher Education

Higher education institutions today face a multitude of complex issues, pertaining to the quality of education, compliance with global standards, accreditation levels, funds and grants, and more. In the midst of this, student experiences and satisfaction levels are the most important attributes which often don’t get the attention they deserve. Institutions have long been experimenting with different techniques to improve these experiences, but for those techniques to yield the desired results, providers require detailed insights into the minds of their students.

To build positive and long-lasting relationships with students, education providers must fully understand what it is the former need exactly, and then provide that. This process involves going back in time to study what happened in the past and using the lessons learned to determine what will happen in the future. Doing so is essential for institutions to realize their unique academic goals. After all, empowering students for success is the end goal for all universities and education providers, so using predictive analytics in this context is simply not optional anymore. With the help of effective predictive analytics mechanisms, education providers can:

  • Identify which students need more support at an early stage
  • Intervene and provide the most appropriate support needed
  • Empower students and institutions to collaborate and share resources with each other
  • Resolve critical challenges with regard to the institution’s performance or across other aspects of the student lifecycle

For universities and educational institutions, analytics can help lay out step-by-step improvement plans for achieving their diverse goals–goals which broadly differ for institutions on the basis of their missions and values. For some, reducing student attrition is a key target, while increasing enrolment rates is the primary objective for some. And, for others, getting higher alumni grants is a core purpose. Identifying these myriad goals beforehand and then leveraging the right data to achieve them is exactly what predictive analytics can deliver for higher education providers. In a pressurized environment, the right analytics is ultimately what can help convince students and parents about the merits of choosing an educational institution and demonstrating the ROI.

Predictive analytics: Delivering impact beyond the student

While students are undoubtedly the most important pillar for higher education institutions, predictive analytics also helps the latter look beyond student experiences. Armed with data, educators can study the implications of their existing systems and structures,  many of which have been around for a long time and require an overhaul. Legacy institutions, in particular, have to contend with this issue. While a lot of them often require revamping of faculty, curriculum and facilities, they don’t really know where to start.  Hence, they simply overlook critical imperatives for initiating improvements.

This is where analytics programs can step in and provide a scientific mechanism for collecting and studying data that is spread over a time period. Viewing data in isolation often leads to half-baked and misinformed decisions. Modern predictive analytics tools now come equipped with visually appealing graphical reporting tools that not only deliver insights in real time, but also make it simple to devise corrective steps of action. All steps are designed for improving collective institutional performance by consolidating varied data channels and tying them together in the form of designated metrics that determine how close or far one is from executing their strategic vision.

The idea here is for education providers to enjoy three major benefits–data, intelligence and action–while creating their plans and offerings. For instance, some institutions can use such data to understand why a few of their campuses from specific regions are witnessing greater dropouts vis-à-vis other campuses, or even the national average. Similarly, an institution can analyze its overall or departmental performance and find out where it is falling short in education delivery and what it needs to do for better accreditations and reputation management.

Conclusion

In today’s day and age, data is the currency of the world. Predictive analytics is the glue that holds this data together and makes sense of the same. For higher education providers, such data encapsulates student journeys from the first step till the last. Predictive analytics can help them determine which steps need overhaul or recalibration, and how they can add value across this cycle in line with their strategic objectives. Building a culture of performance starts from within, and institutions are waking up to this reality as this culture is then passed on to their students. For this purpose, neglecting analytics to deliver education is simply not an option anymore.

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