Higher education institutions are always seeking to improve the services that they offer to their students. This is essential for ensuring that courses are effective, that they continue to provide a high-quality student experiences and that they remain valuable to their regions and to society whilst delivering financial and reputational stability for the institution itself.
In recent years, we’ve seen a rapid uptake from the sector in using learning analytics data to help understand and enhance not only educational delivery, but to make information-led decisions and perhaps most importantly, provide students with insight to assist their own success.
What do we mean by the term Learning Analytics?
The concept of learning analytics revolves around the analysis of data generated by and about learners, their interaction in their learning and the contexts. This can be a combination of on and offline interactions with their participation in learning but in summary the data typically presents a trace or digital footprint that represents a student’s engagement in academically purposeful activity. Learning analytics can therefore help to analyse engagement in courses (use of various resources such as libraries or online resources; attendance to class, labs or virtual lessons, participation in quizzes, assessments, submission or learning materials and any interaction with their academic activities and even the outcomes of their work).
Used in this way, learning analytics can be used to measure engagement at University, faculty/department, school, course, module, or individual student level. At Kortext, we refer to this as engagement analytics. Changes in engagement behaviour such as reduced or no engagement has consistently provided an early warning sign to a student that may be struggling, or potentially considering withdrawing from the course. This provides an academic tutor an opportunity to find out how the student is doing, why their engagement has changed and offer more proactive and personalised support.
It can also be useful for any member of staff such tutors and programme leads to understand teaching methods that are particularly effective, areas in the course or resources that are more engaging that others, and for students, information about how they learn most effectively and ways they can improve.
Why is Learning Analytics so important in Higher Education?
Despite challenges facing the sector such as digital transformation, policy change, student fees, increasingly diverse student populations and the lasting effect of COVID there is great pressure on getting results.
Learning analytics offers a critical tool for institutions to gain a better understanding of how students are progressing in the moment. With this insight, university staff and their students can easily identify areas of concern and interest and make data driven decisions in higher education to maximise success.
What are the Benefits?
Learning analytics surfaces where there are disparities in student wellbeing, attainment and continuation, thereby enabling universities to develop appropriate initiatives to address those disparities and to support every student to maximise their learning potential.
University leaders can gain a consistent and holistic view of student engagement to build a deeper understanding of how students engage in their studies, the effectiveness of course, the resources they use and the potential risk of (preventable) early withdrawal. The data further enables institutions to develop creative and innovative ways of addressing gaps in engagement and attainment suitable for students in different groups or with different characteristics, without labelling or predetermining risks that may never manifest or which cannot be explicitly linked to a particular characteristic.
Academic tutors can identify students who show signs of risk to progression, initiate timely student interventions with precision and even reflect on the impact that has made on each individual student to develop measurable best practice.
Providing engagement data to students enables them to co-curate their learning and reflect on their own engagement, gaining insight into their performance and the relationship between their engagement and their outcomes.
Data used in this context is empowering to the entire community optimising the learning journey by providing the opportunity for more proactive, personalised and precision outreach, pragmatic conversation and reflective learning opportunity.
What does StREAM by Kortext offer?
Leading the sector, Kortext provides learning analytics through the StREAM platform. Our powerful, proven and unique engagement algorithm analyses and collates university data that represents students’ participation in academic learning such as log-ins, submissions, attendance, e-book use, VLE data, library loans, and converts this into a simple measure of engagement that mobilises actions.
A daily engagement score is displayed using simple and intuitive dashboards available to both students and staff with automated alerts that help to spot changes in student behaviour and encourage action. Everything in the platform is designed to make it easier to support students to reach their full potential.
When it comes to helping students to get the most out of their courses, achieving the best results possible, and ensuring that the university continues to provide high quality experiences, learning analytics is a powerful and effective tool that cannot be ignored. By helping students to be informed and learn as effectively as possible, support academics to teach as effectively as possible, and identify potential problems early and with precision, learning analytics system from Kortext is vital for any modern higher education provider.
