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We are entering the decade of AI and quantum environments that will reshape higher education. 

Too often, we look ahead assuming that the technologies and structures of today will be in place for years to come. Yet a look back confirms that change has moved at a dramatic pace in higher education.

• Three decades ago, online learning had not yet emerged in any meaningful way — the Web wasn’t even in place. Now we are approaching 1.75 billion websites.
• Two decades ago, the first full-internet-access smartphone was introduced in Japan; now there are more than five billion users of smartphones around the world.
• A decade ago, the first MOOCs were delivered to relatively small audiences in the hundreds or couple thousands; now there are more than 100 million students taking 11,400 classes at scale from nearly 1,000 universities.

Reviewing the incredible progress each decade brings makes me wonder, if I knew at the beginning of the decade what was coming, how might I have better prepared?

Make no mistake, we have crossed the threshold into the fourth industrial revolution that will most markedly advance this decade through maturing artificial intelligence, ultimately driven by quantum computing. The changes will come at an ever-increasing rate as the technologies and societal demands accelerate. Digital computers advanced over the past half century at approximately the rate described by Moore’s Law, with processing power doubling every two years. Now we are entering the era of Neven’s Law, which predicts the speed of progress of quantum computing at a doubly exponential rate. This means change at a dizzyingly rapid rate that will leave many of us unable to comprehend the why and barely able to digest the daily advances that will describe reality. New platforms, products and processes will proliferate in this new decade.

That includes higher education. The centuries-old model of the faculty member at a podium addressing a class of students who are inconsistently and inaccurately taking notes on paper or laptop will seem so quaint, inefficient and impractical that it will be laughable. Observers in 2030 will wonder how any significant learning even took place in that environment.

Semesters and seat time will not survive the coming decade. Based in 19th- and 20th-century societal needs, these are long overdue to pass away. The logical and efficient structure of outcomes-based adaptive learning will quickly overtake the older methods, doing away with redundancy for the advanced students and providing developmental learning for those in need. Each student will be at the center of their learning experience, with AI algorithms fed by rich data about each student mapping progress and adjusting the pathway for each learner. This will lead to personalized learning where the courses and curriculum will be custom-made to meet the needs of the individual learner. Yet, it also will also serve to enhance the social experience for learners meeting face-to-face. In a report from Brookings on the topic, researchers stated that “technology can help education leapfrog in a number of ways. It can provide individualized learning by tracking progress and personalizing activities to serve heterogeneous classrooms.”

Early implementations of adaptive learning in the college setting have shown that this AI-driven process can result in greater equity success for the students. In addition, the faculty members see that their role has become even more important as they directly interact with the individual students to enable and facilitate their learning.

Increasingly we are gathering data about our students as they enter and progress through learning at our institutions. That big data is the “food” upon which artificial intelligence thrives. Sorting through volumes and varieties of data that in prior decades we could not efficiently process, AI can now uncover cause and effect pairs and webs. It can lead us to enhancements and solutions that previously were beyond our reach. As the pool of data grows and becomes more and more diverse — not just numbers, but also videos and anecdotes — the role of quantum computing comes into play.

While it is unlikely we will see quantum computers physically on the desks of university faculty and staff in the coming decade, we certainly will see cloud use of quantum computers to solve increasingly complex problems and opportunities. Quantum computers will interact with digital computers to apply deep learning at an as yet unseen scale. We will be able to pose challenges such as “what learning will researchers need to best prepare for the next generation of genetic advancement?” Faster than a blink of an eye, the quantum computers will respond.

It turns out that major developments are occurring every day in the advancement of quantum computing. Johns Hopkins University researchers recently discovered a superconducting material that may more effectively host qubits in the future. And Oxford University researchers just uncovered ways in which strontium ions can be much more efficiently entangled for scaling quantum computers. Advancements such as these will pave the path to ever more powerful computers that will enable ever more effective adaptive, individualized and personalized learning.

We know that change is coming. We know the direction of that change. We know some of the actual tools that will be instrumental in that change. Armed with that knowledge, what can we do today to prepare for the decade of the 2020s? Rather than merely reacting to changes after the fact, can we take steps to anticipate and prepare for that change? Can our institutions be better configured to adapt to the changes that are on the horizon? And who will lead that preparation at your institution?

 

This article originally was published in Inside Higher Ed’s Inside Digital Learning blog.