Scalability: At the core of this challenge is the need to scale the human attention so central to learning.

Adaptive tutors help students help themselves, allowing students to practice what they’ve learned and receive detailed, personalized feedback on that practice without requiring human intervention. Students get more “time on task” and teachers can focus their attention on meeting students’ more human needs—for encouragement, motivation, and the development of the habits of effective scholarship.

As the world-wide demand for higher education increases, adaptive systems will allow us to increase access to individualized learning processes, allowing us to reach new populations of learners at more manageable cost.

As exponential increases in raw computing power and advances in artificial intelligence continue unabated, we can expect their technologies—which have already crossed the threshold of utility—to become an increasingly integral part of students’ education with each passing year.

As my colleague Lou Pugliese, managing director of the Action Lab at Arizona State University, has stated, “adaptive systems transform digital learning to effectively address challenges including varying student learning ability, diverse student lifestyles, and limitations on faculty time or other resources.” As these technologies are able to capture ever more detailed and comprehensive data on the learning activity of millions of students, the feedback loops these systems facilitate will help us develop an increasingly detailed understanding of how students learn and how we can advise them during their journey.

Scaling this key component of instruction into the millions of students is central to its development. If you want to use technology in education, scale is your friend, not your enemy.

Traditional education models run up against barriers in multiplying resources like faculty and physical class space. The more students you need to reach, the more expensive the conventional enterprise becomes. Technology has the very real potential to reverse that equation.

Why Scalability is Critical for the Future: Scalability is a solution to an unsustainable model in which individual professors are expected to create individual digital experiences at cottage-industry scales.

The majority of today’s digital learning experiences are crafted by individual professors, working in near isolation, one at a time. It’s unreasonable to expect that such experiences can compete with resource-intensive experiences developed by teams of instructors and learning specialists aimed at supporting millions of students.

As these next-generation experiences emerge, faculty will welcome the increased support and students will embrace digital learning experiences whose usability and efficacy rival the best experiences on the internet.

Other Trends

Other trends emerge from adaptivity and scalability, including continuous and dynamic improvement for both the learner and course.

A traditional course only assesses student performance at intervals, whenever tests or papers are graded. An adaptive learning system is making assessments at every interaction, which allows the student to get any needed additional help in real time or to move ahead faster if everything is mastered. The data flowing back can be captured and help teams to make improvements to the course even while the scale reduce costs.  All of which will help secure a continued place for adaptivity and scalability in the trend tool kit of higher education.

About the Author:

Adrian Sannier is the chief academic technology officer for EdPlus at ASU and a professor of Practice in the School of Computing, Informatics, and Decision Engineering at Arizona State University. He is part of the ASU team pursuing an ambitious program of general education reform that Inside Higher Education called “ground zero for data-driven teaching in higher education,” combining Big Data, social networking, and evidence- based instruction to drive better student outcomes at scale.


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