The accumulation of data in the college setting, plus better hardware and software for putting it to work, means the education community can now make better decisions, retain and educate students with greater success and position themselves for growth in a world of changing demographics, economics and environmental concerns. Here’s a look at digital transformation in higher education, and how it is improving it.
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Artificial intelligence delivers more personalized learning experiences
There are two very big (and very old) problems with the communal learning environment — the classroom — that technology is slowly helping us solve. They are as follows:
- The student-to-teacher ratio can leave some pupils behind for want of personalised curricular pacing and attention.
- Not every student learns the same way or uses the same methods to retain information.
Artificial intelligence is already helping to bring both of these shortcomings of traditional education back into balance. But how?
Because colleges and universities increasingly use digital platforms to present course materials and facilitate exams, AI services could easily interface with these dashboards to provide professors and other faculty with detailed and highly useful information. This data can cover how each pupil is advancing and where different students might ‘branch off’ from the rest — in terms of their aptitudes and interests — and into other related fields and disciplines.
It may sound complicated, but the research behind it is anything but: Researchers have long observed that in a “standardized” learning environment, individual students will interpret and apply the same material in different ways, in real-time, and apply it to their own specific fields of study.
In other words, an AI platform could help tailor a civics course so that it applies to both accountants-in-training as well as civil engineers. It could then plot a course to accreditation for both types of learners. Most importantly, it will ensure each student receives the information that’s most relevant to their personal studies and that adapts to their style and pace of learning.
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Machine Learning Improves Retention and the ‘Customer Experience’
Student retention can be a problem at small and large universities alike. You’ll find rather few colleges with retention rates below 60 percent, but that doesn’t change the fact that many of them have a steep hill to climb to match the schools with the best knack for retention.
The good news is, schools everywhere these days have a great deal of data already at their fingertips. It’s helping apply data science to the problem of seeking out and marketing to potential high-caliber students, matching them with schools and aid packages that make sense for their socioeconomic background and generally ensuring the entire on-boarding experience is a pleasant one.
Since we know students who successfully complete even one full semester are likely to continue their studies and graduate, it makes good sense to use every tool at our disposal to ensure that these early semesters go well.
That’s why some schools, including Deakin University, are turning to big data companies like IBM — and their in-house AI, Watson — to help ease incoming students’ transitions to on-campus life.
Among other tasks, Watson serves as an always-available digital assistant for students. It can, in real-time, answer questions about admissions, financial aid, parking permits, dorm life, campus living, getting around town and much more.
The sheer culture shock of transitioning to full-time education can be a big one, but having reliable answers to common and uncommon questions can go a long way toward helping students feel at home. So that is one benefit of digital transformation in higher education, it helps students settle in.
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Campuses get smarter thanks to the Internet of Things
Digital transformation in higher education also applies to the Internet of Things, or IoT.
Our telephones, homes and cars are already pretty smart. Soon, our college campuses will be too, thanks to the IoT.
What does a ‘smart classroom’ or a ‘smart dorm building’ look like? For a start, you can expect more and more colleges to invest in intelligent thermostats and lighting systems that can be programmed to reflect the ideal conditions for the instructor, the nature of the instruction or the resident of the dorm room. When a room is unoccupied, its temperature and lighting can drop. At times when classes are scheduled, or even when spaces receive unannounced visitors, the systems can return to the users’ preferred settings.
An LED lighting conversion saved the University of Michigan-Dearborn $21,000 per year just on their parking garage. A smart lighting system will save even more.
The IoT will also facilitate seamless, campus-wide communications and help decision-makers pore over more information than ever before. For example:
- IoT-powered mesh networks across college campuses will ensure that there are no connectivity ‘dead zones.’
- Remote sensors can gather data about temperature, the local water table, noise levels, on-campus foot and vehicle traffic and much more to facilitate efficiency-minded and eco-focused infrastructure improvements.
- Smart whiteboards in the classroom and across campuses will provide blank canvases for instructors, promoters, clubs, school leadership and others to give essential information, deliver breaking alerts and promote upcoming events, all without regularly changing physical signage.
These smart universities may well end up looking a lot like smart cities. And for college life especially, there’s an added bonus of security-mindedness.
Campus centers and dorm buildings are already protected by key fobs or card-based security systems, but expect smarter IoT-based security solutions to include remote monitoring and biometric-based authentication before too long, as a matter of course.
The Digital transformation in higher education is just beginning
We touched only briefly on some additional ways to put digital technologies to work, including in college marketing initiatives. Whether it’s using data from web and social traffic to market to students with particular interests or applying machine learning to create the most timely and relevant courseload for each student, expect artificial intelligence, big data and other connected technologies to make a lasting mark on how — and where — we learn.
