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Adaptive Learning | Feature
Adaptive Learning: Are We There Yet?
Partnerships between tech companies and publishers are turning an ed tech
buzzword into a reality, but, as one expert says, "It's going to take some time
to get it right."
By John K. Waters
05/14/14
For more than a decade, K-12 educators have been hearing about the potential of
adaptive learning, an approach to instruction and remediation that uses
technology and accumulated data to provide customized program adjustments based
on an individual student's level of demonstrated mastery. But interest in
adaptive learning has been heating up in the last couple of years, thanks to new
attention from the Bill and Melinda Gates Foundation, new partnerships among
education publishers and adaptive platform providers, and a growing list of
product vendors. Along with that increasing interest and expanding vendor
landscape has come a fair bit of confusion about exactly what the term "adaptive
learning" means. In conversation, it's almost synonymous with "personalized
learning," but in practice, these are different concepts, and K-12 districts
investigating systems that promise to deliver adaptive learning should
understand that difference.
What Is Adaptive Learning, Exactly?
According to Adam Newman, founding partner of Education Growth Advisors (EGA), a
strategic advisory and consulting firm and investment bank focused exclusively
on the education sector, "'Personalized learning' is really an umbrella term."
In two recently published white papers commissioned by the Gates Foundation
("Learning to Adapt: Understanding the Adaptive Learning Supplier Landscape" and
"Learning to Adapt: A Case for Accelerating Adaptive Learning in Higher
Education"), EGA researchers — Newman among them — defined "personalized
learning" as a "pedagogical method or process that draws on observation to
inform tailored student educational interventions designed to increase the
likelihood of learner success." As Newman said, technology isn't actually
required for personalization, but the tech makes it possible to personalize at
scale.
K-12 educators have been personalizing learning in their classrooms for decades
without technology: If Jesse is having trouble reading, the teacher assigns her
some extra reading in Chapter Two, for example. Personalized learning covers a
range of approaches and models, Newman said, including competency-based
learning, differentiated instruction and tutorial models — as well as adaptive
learning. "So you can think of adaptive learning models as one approach along a
spectrum that enables personalization," he said.
In "Learning to Adapt," EGA researchers went on to define "adaptive learning" as
an approach to creating a personalized learning experience for students that
employs "a sophisticated, data-driven, and in some cases, nonlinear approach to
instruction and remediation, adjusting to a learner's interactions and
demonstrated performance level, and subsequently anticipating what types of
content and resources learners need at a specific point in time to make
progress."
Types of Adaptive Learning
The EGA researchers concluded that technology vendors offering truly "rigorous
adaptive learning solutions" leverage numerous areas of academic research,
including intelligent tutoring systems, machine learning, knowledge space
theory, memory and cognitive load theory. They also divide adaptive approaches
into two categories: "facilitator-driven," which refers to products that provide
instructors with actionable student and cohort profiles — essentially
dashboards. This approach is content-driven, which means that the dashboard
output links a specific course's content inventory "within a system of standards
or learning sequences."
The other approach — the one most people are talking about when the conversation
turns to adaptive learning — the researchers call "assessment-driven." In this
approach, the system provides close-to-real-time (sometimes called "dynamic")
adjustments of the instructional content. Facilitator-driven systems provide
instructors with information they can act on; assessment-driven systems make
their own adjustments. In order to provide these adjustments, the researchers
said, assessment-driven systems must be correlated dynamically with assets,
items and learning objects to standards, outcomes or other frameworks. Another
essential difference: the assessment-driven model allows students to move the
course individually or in a group, without instructor interaction. Newman added
that the two approaches are not mutually exclusive, and both might be found in a
single product or system offering.
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