Data analytics can help revive traditional higher education
Economists agree that education is one of the primary drivers of economic development. An economy blessed with intellectual minds will certainly achieve higher and more sustainable economic growth than its counterparts.
That’s why from ancient times right through to medieval times, many of the leading civilisations prioritised and promoted the development of scholars by building cutting-edge educational institutions (at least for that period) like the University of Ancient Taxila, Cambridge, and Oxford—some of which still stand today.
Since these ancient universities, higher education has grown significantly, driving advances in technology, literature, science, architecture, and more along the way.
That said, with the introduction of the internet, higher education has become more accessible. Modern students have access to unconventional academic avenues to further their knowledge.
Today, traditional higher education is at a critical juncture. With the rise of web-based learning, students are more likely to drop out of traditional higher education systems to pursue education via more convenient and sometimes more insightful channels.
In recent years, the higher education dropout rate has increased steadily. In the USA, almost 40% of students from each academic year are dropping out of colleges and other higher education institutions.
All this begs the question: How can traditional higher education institutions stay relevant in this digital boom? Big data analytics might hold the answer to this question.
In this post, let’s explore the role of data analytics in modernising higher education.
Why is traditional higher education a less obvious choice now?
Before diving into what traditional higher educational institutions can do to remain competitive and relevant, it is important to understand why they are becoming a less obvious choice for modern students.
According to a study, higher education remains inaccessible for many students due to high costs. In fact, in the USA, an average student has a debt of $32,731 when they complete their higher education through the traditional route.
Compared to this, non-traditional channels are more affordable for students of almost all backgrounds.
Other reasons for the loss of popularity of traditional education include the lack of integration of modern learning and teaching tools, out-of-date curriculums, and a lack of real-world skill development.
How can data analytics help traditional higher education?
- It can help develop relevant and personalised curriculums
Universities and other traditional higher education institutions sometimes persist with a tried and tested curriculum for an extended period. While this can help standardise the teaching, learning, and testing process, it doesn’t educate students about the current trends, latest breakthroughs, and empirical findings.
With data analytics, these institutions can identify the most relevant topics to include to create an up-to-date curriculum.
Also, many students benefit from having a personalised study plan that caters to their learning requirements. Data analytics can help educators identify and track the progress of each student in a detailed manner, which helps them personalise the curriculum to make it more comprehensible.
In addition, data analytics can power a more up-to-date skills development programme for students by identifying the skills in demand and providing educators with insights to help improve the existing skills training systems.
- It can help match students with the right course
Many students face a conundrum when deciding what course to pursue in higher education, and a considerable amount of students choose wrong—a leading cause of increasing dropout rates.
With data analytics, higher education institutions can build a recommendation system that considers students’ competencies, skills, interests, and career ambitions and recommends the most suitable course for them.
- Data analytics can help reduce the cost of education
Data analytics can help higher education institutions identify cost-cutting opportunities. While not directly related to the curriculum or other academic activities, this can help these institutions reduce their administrative costs. Universities and other institutions can transfer these savings to reduce tuition fees for students.
This way, more students will have access to higher education while academic institutions will attract more students and increase their revenue.
The University of North Texas, for example, leveraged the power of data analytics to reduce administrative costs by $1 million and transferred the savings to increase their student retention rates.
Data analytics might be the need of the hour for higher education
With increasing competition from non-traditional education channels, traditional higher education is becoming less popular among students, but data analytics can change that.
By integrating advanced analytics, higher education institutions can stay relevant and regain the lost popularity.