The Impact of Predictive Analytics in Higher Education

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While for many a college degree may be the golden ticket to a better job, this incentive alone isn’t enough to stop millions from dropping out of school or delaying graduation. In fact, some universities are experiencing freshman retention rates as low as 47 percent.

On top of the incredibly high dropout rate, the affordability of college continues to be scrutinized. This has put universities under intense pressure to demonstrate a tangible return on investment for students and their parents. The answer to this predicament is a practice called predictive analytics.

Let’s be clear: predictive analytics is not a new concept. Organizations have been using this practice for decades. However, the education industry is just now understanding how to capitalize this practice in a way that truly defines the college learning experience.

Unlocking its potential.

According to a recent report, learning analytics will be one of the largest emerging fields in education. This is not surprising given that it’s a tool that elevates an impactful component to education, which is personalized learning in the classroom.

Personalized learning is a customized learning style based on the needs of each student, and a practice that has been proven to be successful in the classroom. However, this method also brings a series of instructional challenges that are impossible to manage without appropriate technology, especially in classrooms with large student-to-teacher ratios.

That’s why data and predictive analytics play a pivotal role in developing more personalized learning strategies that boost student engagement and improve student outcomes.

By leveraging predictive analytics, educators can identify patterns of disengagement and intervene earlier with higher impact. This practice also helps ensure students receive the right instruction to effectively achieve learning goals. Therefore, the data insights and analysis will help change the conversation for educators regarding how to think about students’ progress and sustain success.

Furthermore, this data also allows professors to understand the engagement and class comprehension of its content, assignments, course design and more. This feedback is incredibly valuable to educators as well as course authors, so they can make adjustments to the course and better understand its efficacy without compromising its integrity.

While this practice can be leveraged at all education levels, it’s vital it be implemented during the more vulnerable years for college students. As stated earlier, the latest trends have shown that only half of all students will leave college with a diploma. And the biggest drop out rate occurs after a student’s first year, with some universities fighting a freshman retention rates as low as 47 percent.

Therefore, universities need to be better equipped to engage students during this time period without compromising academic integrity. Doing so will help ensure students are not deflected while boosting a higher likelihood of retention.

Universities who have leveraged predictive analytics in the classroom have seen a decrease in fail and dropout rates as high as 50 percent. Student success has also improved, while GPAs were better and engagement was at an all-time high.

Since this practice is so novel, there is a significant shortage of professionals with the necessary expertise to actually mine and interpret the data. According to McKinsey, the United States alone could face a shortage of qualified individuals with deep analytical skills.

That’s why it’s important for universities to seek out experts or partners who can handle this practice ethically and effectively for the betterment of students. Without their assistance, universities might have used more traditional methods to evaluate data, which could lead administrations to leverage this data unethically while curtailing academic success.

The future of higher education.

It’s not surprising that predictive analytics unlocks the key to a new future in education. This practice allows universities to help students map their progress toward a degree, determine their academic pathway and improve skills to enhance their education. And ignoring these technological opportunities that complement our human capacities may lead to a disservice to students.

For those institutions who boast the necessary resources to leverage predictive analytics in the right way, now is the time to unleash these capabilities to drive a more collaborative, student-centric experience. Doing so can create a better learning future.

Brian Rowe is founder and chief executive officer of Perceivant.

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