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Learning analytics in higher education

Institutions are turning to Learning Analytics to increase their bottom line and competitive advantage. In order for educational institutions to differentiate themselves and remain competitive, institutions must identify and understand the needs of their students. Traditional surveys are retrospective and only offer an insight after the fact. Real-time data like attendance, grades, submissions and LMS data provides current and future insights.

Learning analytics in higher education can be used to identify students at-risk, improve completion rates, predict student success after graduation, and even personalise the learning process for students.

Actionable Insights from an Student Attendance Management System - benefits of education technology

There are numerous applications of learning analytics in Higher Education. Below are the three main reasons for universities and colleges:

Efficient student advising

Advisor caseloads are growing year on year. In the US, The National Academic Advising Association (NACADA) found that the national average caseload per full-time professional academic advisor was 296-to-1. The ratio jumped to 441-to-1 at community colleges.

Assigning advisors efficiently and automating communications can greatly reduce the caseload on an individual level.

Early Alert Systems identify at-risk students as early as the first semester and allocate appropriate advisors based on the student’s needs using learning analytics, and strategic workflows.

Manage Enrolment

Learning analytics can help schools forecast the size of incoming and returning classes. Institutions can also narrow their recruitment and marketing efforts so they are only targeting students who are most likely to apply, enroll and succeed. Institutions can use learning analytics anticipate the financial needs of incoming and returning classes to determine whether a student will accept the financial aid award offered to them.

Adaptive Learning

Learning analytics in higher education can modify a students learning route based on their interactions to maximise student success. A one-size-fits-all approach is no longer the only option with instructors now capable of pinpointing students’ learning gaps and customising the academic experience so it can better align with how the student learns.


If you would like to learn more about how learning analytics can benefit your institution, contact us at