PLW-intro-april2013-ver3x - Rice University

wonderfuldistinctAI and Robotics

Oct 16, 2013 (3 years and 10 months ago)

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Personalized Learning

Workshop


2013

Office of the Provost


George R. Brown

School of Engineering


Ken Kennedy Institute for

Information Technology

STEMScopes

Denise Fly

Charmaine St. Rose

Kathryn O’Brien

Cheryl Morehead

Daniel Williamson


o
ne
-
size
-
fits
-
all

learning

o
ne
-
size
-
fits
-
all

learning

o
ne
-
size
-
fits
-
all

learning

t
echnology to the rescue!

Education Tech Investments

Surpassed $1 Billion in 2012


As venture capitalists pour money into educational technology
companies, some wonder whether they are just building a new
bubble.



ed

tech
hype

ed

tech
hype


T
hanks
to the invention of projected
images,
books
will soon be obsolete in
schools.

Scholars
will soon be instructed
through the eye.



-

Thomas Edison

ed

tech
potential

d
ata


(massive, rich, personal)

close
the learning

feedback
loop

p
ersonalized learning

closed
-
loop


students and instructors as active
explorers of a knowledge space


tools for instructors and students

to monitor and track
their progress


adaptation


to each learner

s background,

context, abilities, goals


cognitively
informed


leverage latest findings from the

science of
learning

c
urriculum

(re)design

p
ersonalized

learning

p
athways

c
ognitive science

research

big data

cycles of

innovation

p
ersonalized learning

m
assive

opportunity



but


c
hallenges

remain…

expensive

c
ost to develop one course

supporting personalized learning

can exceed



$
1M


+ several years



t
ypically large
t
eam of

disciplinary specialists

to
hand
-
code

meta data and rules


http://
www.newscientist.com
/article/mg21528765.700
-
the
-
intelligent
-
textbook
-
that
-
helps
-
students
-
learn.html

“While
such results are promising, perhaps it's a little soon to
crown Inquire the future of
textbooks
.
For
starters,
after two
years of work the system is still only half
-
finished
. The
team
plan to encode the rest of the 1400
-
page
Campbell
Biology
by
the end of 2013, but they expect a
team of 18 biologists
will
be needed to do
so. This
raises concerns about whether the
project
could be expanded to cover other areas of science, let
alone other subjects
.”

many educators/systems are reticent to changing
their teaching methods wholesale or overnight


y
et many personalized learning systems require
significant changes or training to use correctly




a
doption chasm

p
eople
want
learning to be
quick

and
easy

p
ersonalized learning systems

can
optimize learning



but what
kind

of learning?




o
ptimizing learning

for machine learning,
data is king


n
ew opportunity
to study how people
learn


massive
, global scale
(millions of students)


entire lifetime of learning (PK
-
24+)


s
ignificant
privacy

issues

(
FERPA, opt
-
out, …)

e
lectronic learning records

l
arge
-
scale platforms

m
achine learning

c
ognitive science

h
uman
-
computer interaction

d
ata security and privacy

s
cal
ing

up

morning

David Kuntz,
Knewton


David Prichard
,
MIT


Steven
Ritter, Carnegie
Learning


Break and Poster Session


Neil
Heffernan,
WPI


Winslow
Burleson,
ASU

Personalized Learning

Workshop


2013

a
fternoon (1/2)

Jascha

Sohl
-
Dickstein, Khan
Academy

Anna
Rafferty, UC
-
Berkeley

Zach
Pardos
,
MIT

Richard
Baraniuk, Rice
University

Break
and Poster
Session

a
fternoon (2/2)

Panel: Data
, Privacy, and

Electronic
Learning
Records

Panel: Cognitive
Science and
Neuroscience in
Personalized
Learning

Breakouts

Breakout
Reports



Personalized Learning

Workshop


2013