Education Week - October 22, 2014 - S6

S6 |
EDUCATION WEEK OCTOBER 22, 2014
n
Taking Stock of Personalized Learning > www.edweek.org/go/personalized
Push for 'Learner Profiles' Stymied by Barriers
The goal is to
generate
detailed digital
portraits of
each student's
strengths,
weaknesses,
and
preferences
to build
customized
academic
content
F
By
Benjamin
Herold
or many proponents
of personalized learning,
the notion of a
digital "learner profile"
is something of
a Holy Grail-tantalizingly
powerful
to imagine, but stubbornly
difficult to actually find.
Just ask Jose P. Ferreira, the ceo
of Knewton, a New York City-based
company that is currently amassing
hundreds of millions of bits of data
on the learning histories of about
2 million American schoolchildren.
The goal is to generate ever-more
comprehensive portraits of each student's
strengths, weaknesses, and
preferences in order to provide them
with customized academic content.
But to date, efforts by Knewton
and other vendors to build a truly
holistic portrait of any one child
have been stymied. The long list of
barriers includes technical hurdles,
turf battles among educational publishers,
lack of clear demand from
schools, concerns about data privacy,
and criticism that their work is
based on a fundamental misunderstanding
of how children learn.
"One day the world's going to
wake up and say, 'Well, of
course I've got a learner
profile that's hosted in
the cloud and goes from
book to book and school
to school and country
to country and gets
smarter and smarter the
more I use it," Mr. Ferreira
said. "We know that's obviously
going to happen. But it's not obvious
to anybody outside of Knewton. So
we've got our work cut out for us."
Harvesting Student Data
Although far from a mainstream
idea, the concept of digital learner
profiles has been around for years.
Its clearest roots are in the healthcare
sector, where electronic patient
records have in recent years become
the norm.
The basic idea is to harvest all
the data students generate while
interacting with the dizzying range
of software and apps now found
in many classrooms in the United
States-every minute spent on a
given problem, every answer to
every question, even every click and
hover-then store them in a single
place.
From there, the data can be analyzed
for signs that students have
mastered a given standard or concept,
as well as for evidence of the
optimal ways in which each student
learns.
In theory, the resulting profile
can then be used by teachers to target
instruction based on individual
students' needs and preferences.
Software can also analyze the information
in order to recommend the
specific piece of content in the exact
format at the precise time that algorithms
determine is most likely to
help an individual student master
the specific concepts at hand. Some
evidence suggests that such analyses
may yield new and unexpected
insights into how different topics are
best taught.
"It's the type of information that
parents and teachers want to know,
and frankly, should know," said John
Bailey, the executive director of the
Tallahassee, Fla.-based nonprofit
Digital Learning Now, who co-authored
the 2012 report "Data Backpacks:
Portable Records & Learner
Profiles."
Online adaptive tests, now in widespread
use, rely on similar principles,
but on the much smaller scale of an
individual assessment. (See story,
page S24.)
Likewise, private-sector developers
of educational software such as
Amplify, Dreambox, and Khan Academy
now use proprietary personalized
learning platforms to generate
robust profiles of individual students,
but those portraits are generally confined
to a particular course or suite
of content.
And makers of K-12 learning management
systems are increasingly
trying to integrate the student-learning
data generated from a variety of
sources, but progress has been halting,
and most lms software lacks the
sophisticated predictive algorithms
that actually put all that data to
work.
So for now, the ideal learner profile-a
digital dossier that stitches
together everything a student does
across multiple textbooks, inside
school and out, over the course of
multiple years, and feeds software
that uses the data to make recommendations
for individual students-
lives mostly in the imaginations of
those who believe the concept has
the power to transform education,
for better or worse.
Few companies are searching as
aggressively as Knewton for a way
to make the vision a reality.
"If we have not just a semester's
worth of your math [learning] history,
but every semester, and we
can tie that to your science history,
we can tell you things like, 'You're
struggling in physics because of your
math skills,' " Mr. Ferreira said. "In
the whole history of education up
until now, those have been invisible
failures."
Critiquing the Vision
But for Yong Zhao, such grand
pronouncements would mostly be
annoying, if they weren't so dangerous.
The
professor and presidential
chair in the college of education at
the University of Oregon, in Eugene,
is among those who believe
that the notions underlying Knewton's
work-that the bulk of what
students should learn in school
amounts to a series of discrete concepts;
that mastery of those concepts
is best "acquired" in a linear,
orderly fashion; and that algorithms
can analyze digital data to predict
Jose P. Ferreira is the CEO
of Knewton, a New York
City-based company that is
amassing hundreds of
millions of bits of data on
the learning histories of
about 2 million K-12
schoolchildren in the United
States to build "learner
profiles" for them.
the optimal path for students to follow-are,
at best, unsupported by
evidence.
"Children have feelings. They're
social beings. And they learn best
by interacting with others," Mr.
Zhao said. "By putting too much
blind faith in this data, we risk
treating learning as a mechanical
process and not a human endeavor."
The potential costs, he said, include
inaccurate or misguided
judgments about children, a lack of
appreciation for how mistakes and
mental detours can actually aid
the learning process, and time and
money diverted from "the things
that parents and educators actually
care about," such as small class size.
That's probably the highest-order
critique of the kind of comprehensive
learner profile for which Knewton
and others advocate. But it's far
from the only one.
Even some proponents of big
data in K-12 schools say that many
software companies purporting to
personalize education by profiling
PAGE S8 >
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Education Week - October 22, 2014

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