As higher education institutions face increased enrollment and financial challenges and the looming enrollment cliff, there’s been a renewed and critical focus on what institutions can more directly control—student retention.
In the last decade, institutions have been grappling with several student success challenges, including underutilized institutional resources due to lack of engagement, siloed processes across departments, lack of data governance and integration, and the inability to track remediation efforts. In response, many institutions are modernizing how they track and engage with students and adopting cross-functional, data-driven student success models. In addition to student success, there’s also an increased interest in optimizing and unifying institutional best practices and data around student advising, degree planning, scheduling, and degree audit.
Let’s explore three key trends changing and modernizing institutional advising and student success.
Historically, advising and student success have not been well defined at the institutional level, and academic outcomes have often varied across institutions and even departments. As such, many institutions are moving away from highly siloed advising and academic planning models to more holistic and centralized approaches. One of the factors driving this trend is the imperative for consolidated student success data.
Institutions are finding that decentralized advising structures make data aggregation extremely challenging, especially for institutions that have not invested in data governance and integration. With modern student success and analytics solutions, institutions gain access to real-time academic data that spans the campus, including student system data as well as engagement, behavioral, and LMS data, to get a 360-degree view of the student.
In an effort to increase student engagement and participation, student success initiatives are becoming less transactional and more focused on the student. While student success solutions and programs have historically been developed with advisor needs top of mind, modern approaches are much more student-centric and focused on student self-service. As such, advising and academic planning are shifting from a prescriptive approach to a more holistic and developmental model where students have greater responsibility and control in planning their academic journey. Rather than advisors telling students what courses they need to take, students are more actively engaging in their academic planning, and advisors are there to guide them with an eye on their interests, strengths, and career goals.
Modern student success solutions are unifying advising, degree planning, course scheduling, registration, and degree audit, which ultimately enhances the user experience. Students can view their current academic plan and how they’re progressing toward graduation online (via mobile or web). They no longer have to go through their advisor to get an update on their progress. Institutions are also working to further engage with students and increase student communications with advising staff and faculty.
Using student success analytics to optimize advising efforts and increase retention and learning outcomes is a growing trend across higher education. As institutions navigate financial and retention pressures, the need for data-driven decision making has become critical.
Historically, student analytics required institutions to stand up a data warehouse that aggregated disparate data from across the institution, including student data (advising, persistence, academic planning), LMS data, engagement data, and more. However, some modern platforms leverage artificial intelligence (AI) and machine learning (ML) to offer more comprehensive support for analytics that can increase retention by identifying students who are at risk early in the process so staff can intervene. Institutions can use historical data to understand factors that are impacting success for individuals and specific groups of students. By combining all aspects of student retention into a single solution, institutions can access many different types of analytics—including course demand, course load, instructor analytics, student engagement analytics, and more—all of which help institutions better serve their students.
The aggregation of multiple student success data points into a single solution gives advisors and faculty an accurate pulse on the academic health of each student. It’s critical that institutions have the ability to assess student interventions to determine what programs are working at an aggregate or individual level. Likewise, it’s imperative that institutional advisors understand what’s driving successful outcomes and what remediations aren’t working.
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