Four Ways Analytics Can Drive Student Success in Higher Ed
With changing demographics, increased competition, and rising costs, it is more important than ever for institutions to focus on engaging with students and helping them succeed. But how do you track and engage with students throughout their higher education journey? By using data.
Higher education is one of the most data-rich industries, as schools have mountains of information on students as well as their institution. However, this richness has largely been untapped, with data lingering in a variety of silos. With new technology, those silos are now readily available to be compiled, processed, and analyzed, making it easier for institutions to help students.
Leveraging analytics can make higher education institutions more agile, allowing them to incorporate data into their decision-making processes and proactively adapt to market changes. Meanwhile, rich information can give organizations more insight into student activity and engagement, enabling institutions to identify at-risk students and respond accordingly. For example, colleges and universities may find patterns associated with difficult courses which are preventing students from progressing.
Let’s take a closer look at how schools can and should leverage data to increase student success.
1. Recruit Best-Fit Students
Competition for the best students is tough, with institutions finding their peers aggressively recruiting prospects. Identifying applicants whose priorities “fit” with an institution’s mission does need to be like finding a needle in a haystack. The search and outreach can be more focused and successful by using analytics.
Schools can use analytics to identify the characteristics and behaviors of successful students at their institution and focus their marketing efforts on prospective students that meet similar criteria. This will help universities improve the chances of recruiting successful students, while simultaneously boosting the return on marketing investments.
2. Optimize Financial Aid
Schools now have access to financial aid data models. Incorporating these and other analytics tools into their financial aid processes means institutions can send out compliant, accurate award packages faster. By offering more intelligent packages to a broader range of students and prospects, schools can gain a critical competitive advantage over peers when securing the best students.
3. Increase Retention
Retaining students is critical, but institutions need to look beyond GPA, test scores, and academic performance. With analytics, schools can aggregate student information from disparate academic and administrative systems across campus to create comprehensive student profiles. The result is a 360-degree view of each student—from academic performance and extracurricular engagement to financial aid and behavioral and demographic information—providing deep insights into probabilities of success. This visibility also makes it easier for schools to identify at-risk students, as well as the factors leading to those complications, and take the necessary steps to enable student success.
4. Improve Student Advising
Many of today’s students have complex academic paths to graduation and require clear academic paths toward completion. Without proper guidance on how to get there, student success rates may dwindle. If students take classes that do not apply to their degree, for example, they can end up without enough credits at graduation time. By incorporating analytics into academic advising, schools can provide advisers with detailed insight into data relevant to students as well as prediction models that can help boost success and provide clear guidelines for students.
We are in the early days of widespread adoption of data and analytics in higher ed today. Developing a strong culture of student-centric services with data analytics and a focus on measurable outcomes will create significant value for students.
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