Education Week - January 13, 2016 - S4

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WEEK
13, 13,
2016
EDUCATION
WEEKJanuary
January
2016
| EDUCATION
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BIG DATA OR
BIG BROTHER?

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and connections relating to human behavior and
how complex systems function.
Analytics generally refers to the process of collecting such data, conducting those analyses, generating corresponding insights, and using that new
information to make (what proponents hope will be)
smarter decisions.
For years, public schools and ed-tech companies
have experimented with both, usually with two goals
in mind: to better personalize instruction, by customizing the learning experience to each student's individual skills, abilities, and preferences; and to facilitate more data-driven operational decisions.
Inside school systems, advances have been made.
It's now common, for example, for classrooms to use
learning software and digital games that generate
extensive data that can be mined for evidence of student learning. At the macro level, districts routinely
analyze large data sets containing information on
students' academic performance, attendance patterns, and even involvement with other public agencies. The results are used to predict which students
are likely to become disengaged or drop out of school,
then to intervene accordingly, among other purposes.
In the ed-tech industry, meanwhile, big data and
analytics are everywhere. Companies ranging from
Khan Academy to Pearson collect and analyze reams
of information on how millions of students interact
with digital content. Other companies promise to
help district administrators use big data to predict
everything from which candidates for teaching jobs
are likely to have the biggest impact on student-test
scores to where population growth will require that
new school buildings be built in the future.
But experts say such initiatives have mostly resulted in small pockets of innovation or incremental shifts to existing practices, rather than systemic
transformation.
One big reason: Big chunks of the data currently
in use are either stored on paper or in teachers'

ward-thinking NBA teams collected were fairly
limited, said Benjamin Alamar, a former executive
with the Seattle SuperSonics (now the Oklahoma
City Thunder) and the current director of sports
analytics for the giant sports-entertainment company ESPN Inc.
Only a handful of franchises were doing any kind
of complex statistical analysis of the information that
was collected, Alamar said. Even those teams often
stored their information in scattered spreadsheets
and databases used by different people for different
purposes. Information-related turf wars between departments were common. Many teams suffered from
a lack of consensus around which metrics of success
really mattered. Inconsistent ways of formatting and
handling data exacerbated all those other problems.
The end result was that harried decisionmakers-
in the NBA's case, coaches and general managers-
often struggled to access new forms of information,
leading them to rely instead on established habits.
"The challenges are the same from industry to
industry," Alamar said.

Changing the Game
In a short period of time, however, the NBA has
been transformed.
To staff their new analytics departments, pro
basketball teams now compete with tech giants
and blue-chip management-consulting firms for
data scientists with computer-programming skills
and deep knowledge of advanced statistics.

he emergence of big data and
analytics in public education is
bringing new urgency to the national
debate over digital privacy.
Take AltSchool, an education startup that
is adapting some of the passive-observation
technologies already in use in such fields as
consumer technology, professional sports,
and retail sales. Those approaches include
constantly running video cameras and audio
recorders, and the use of motion-tracking and
facial- and speech-recognition software.
The idea is that more and better information
on students, collected unobtrusively as they
go about regular learning activities in the
classroom, might help make education more
personalized, powerful, and efficient.
But where proponents see potential for
innovation, others see big trouble.
It's especially problematic that big-databased experimentation is almost entirely
unregulated, said Joel Reidenberg, a school
privacy expert and law professor at Fordham
and Princeton universities.
"The extent to which a total surveillance
environment affects a child's learning, psyche,
and personal growth is uncharted territory,"
Reidenberg said. "We need development of
ethical principles for the use of these data, as
well as objective review mechanisms."
That kind of independent, third-party review
of ed-tech companies' plans for experimenting
with big data and analytics doesn't appear
likely anytime soon. The conversation is only
just beginning, Reidenberg said, because big
advances in data science are so new.
In the meantime, parents and citizens
should be aware of possible harms, said Elana
J. Zeide, a privacy research fellow at New York
University's Information Law Institute. "There
is the potential that ubiquitous surveillance
might chill intellectual exploration," she said.

Weighing the 'Psychic Cost'

"We don't want to improve some aspects of what schools do. We want a
different kind of universe in which schools can exist 30 years from now."
MAX VENTILLA
CEO, AltSchool

heads. And much of the digital information in use is
generated via students' on-screen and online activity, which even those in the ed-tech world acknowledge can capture only a limited slice of what constitutes real learning.
Other barriers exist, too. Even when new technologies have been introduced into classrooms,
teachers have been slow to change the ways they
teach. Districts have struggled for years to integrate data housed in separate silos. The education
sector is embroiled in debates over how student
information should be appropriately collected,
shared, and used.
The net result is that school officials often settle
for using technology to meet basic compliance requirements, said Jeff Wayman, a former educational
researcher at Johns Hopkins University who now
consults with districts on effective data systems.
"Technology got schools to a point where they can
get done the things that have to get done," Wayman
said. "But in their heart of hearts, I think a lot of developers would say the technology is so much more
powerful than how it's being used."

Parallels With Professional Sports
Other industries have found themselves in analogous positions.
Take, for example, professional sports, including
the National Basketball Association.
Until recently, the types of data that even for-

NBA arenas are now outfitted with sophisticated
camera systems that capture the location, movement,
and actions of every player on the court 25 times per
second. The system has produced a mountain of new
data on such minutiae as the optimal number of
times each player should dribble before shooting.
And teams are building new information-management systems that integrate such data with
quantitative game-performance results, qualitative scouting notes, leaguewide salary information,
biometric data on everything from players' sleep
habits to their exertion levels during practice, and
multimedia files (such as video clips of an individual player's tendencies.)
The game itself has changed as a result. One of
the original insights of the basketball-analytics
movement was that 3-point shots (taken from further out on the court) and layups (taken close to
the basket) produce points far more efficiently than
mid-range shots.
In response, teams have made a series of personnel, training, and tactical shifts, resulting in a
league-wide trend of players taking inefficient, long
2-point shots far less frequently this year than they
did just four years ago.
Now, Alamar said, the challenge for NBA decisionmakers is how to stay ahead of the curve. In an
analytics-driven culture, "you're always growing,
and you're never there," he said.
As vice president of research and development for
PAGE S6 >

Other worries involve the creation of
profiles that could linger beyond their
accuracy or utility; making key educational
decisions based on algorithms that are too
complex for the typical student, parent, or
teacher to understand or challenge; and
the possibility that pervasive monitoring
in schools might normalize the kind of
real-world surveillance that has landed the
National Security Agency in hot water.
For their part, AltSchool officials stress
that there's a big gap between what they're
doing currently and what they may do in the
future. Parents are opting into the AltSchool
model, and scrutiny and debate are welcome,
CEO Max Ventilla said.
"I agree that there is a psychic cost to
monitoring that is quite high, and that needs
to be overcome to justify the monitoring in
the first place," Ventilla said. "But if you
don't allow yourself to even get started, you
preclude a lot of [potentially] good uses of
these kinds of technologies."
So far, though, legislators and policymakers
have mostly struggled to keep up with the
ambitions of the ed-tech sector.
One major example: the actions of onlineservices-giant Google, the former employer of
both Ventilla and AltSchool co-founder and
chief technology officer Bharat Mediratta.
"Google [has] business reasons that cause
it to cozy up to that line in ways that are
going to upset some people," Mediratta said.
"But for us to be successful, we have to make
sure that people trust us with the data we
gather on their children and help them
understand that it will pay off in a much
higher-quality education for their child."
-BENJAMIN HEROLD

http://www.edweek.org/go/digitalprogress

Education Week - January 13, 2016

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