Transaction Management in Database Management System
We Survived the Book: Why Worry About the Internet?
1. We
Survived
the
Book
–
Why
Worry
About
the
Internet?
(A
few
thoughts
on
the
future
of
educa@on)
David
Wiley,
PhD
Department
of
Instruc@onal
Psychology
&
Technology
Brigham
Young
University
CC BY!
7. 15th
Century
English
law
reads:
“whosoever
reads
the
Scriptures
in
the
mother
tongue,
shall
forfeit
land,
caWle,
life,
and
goods
from
their
heirs
forever,
and
so
be
condemned
for
here@cs
to
God,
enemies
to
the
crown,
and
most
arrant
traitors
to
the
land.”
CC BY!
28. 16th
Century
Though
texts
are
less
expensive,
students
aren’t
buying
-‐
and
write
leWers
asking
faculty
to
slow
down
CC BY!
29. 16th
Century
“Lecture
Texts,”
printed
classics
with
very
wide
margins
for
copying
faculty
annota@ons,
come
into
use
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30. 18th
Century
Transcribing
lectures
finally
begins
to
stop,
though
lectures
and
the
transcribing
of
annota@ons
con@nues
CC BY!
31. 18th
Century
Earliest
recorded
use
of
erasable
chalkboard
in
teaching
arts
and
sciences
CC BY!
32. 20th
Century
Purchase
of
textbooks
required
for
class
(though
prac@ced
in
early
1700s
at
Harvard)
CC BY!
33. 20th
Century
Overhead
projectors,
transparencies,
slide
carousels,
computer
projectors,
Powerpoint,
etc.
CC BY!
34. Moral
of
the
Story
The
2nd
most
transforma@ve
technology
of
all
@me
cannot
convince
faculty
to
stop
lecturing
CC BY!
35. If
500
Years
of
Books
…
Can’t
get
faculty
off
the
stage,
why
would
we
believe
that
computers
or
the
Internet
can?
CC BY!
36. Lecture
Is
A
Millennia-‐old
Prac@ce
That
we
just
can’t
seem
to
shake
(including
this
presenta@on!)
CC BY!
37. Faculty
Corrupt
Web
2.0
These
are
technologies
based
on
the
idea
of
democracy
and
equal
contribu@on,
but
faculty
co-‐opt
them
as
lecture
supports
CC BY!
38. (Remember
the
Church
/
Press?)
Instead
of
using
the
technology
to
drive
needed
reforms,
higher
ed
uses
tech
+
policy
to
further
entrench
the
status
quo
CC BY!
39. Reform
from
Within
is
Failing
Will
higher
educa@on
have
its
30
years
war?
CC BY!
76. Educa@on
Relies
Heavily
on
Intui@on
LiWle
choice
without
alterna@ves
So
like
the
“pedagogical
benefits
of
hand
copying
a
text,”
a
mythology
has
developed
around
hunches
CC BY!
77. We
Could
Be
Swimming
in
Data!
Every
computer-‐mediated
interac@on
with
content,
a
teacher,
or
learners
creates
vast
amounts
of
data
CC BY!
78. We
Don’t
Bother
Capturing…
Let
alone
analyzing
this
data
or
using
it
to
support
decision
making
CC BY!
79. What
Kinds
of
Decisions?
Who’s
behind?
Who’s
read?
Who
needs
some
tutoring?
What
do
they
need
help
with?
What
should
I
teach
today?
How’s
my
curriculum
func@oning?
Which
pieces
of
it
need
replaced
or
updated?
Are
my
assessments
too
hard?
CC BY!
80. A/B
Tes@ng
Every
garage-‐based
Mom’s-‐credit-‐card
startup
does
A/B
tes@ng,
pours
over
their
data,
and
adjusts
their
offering
based
on
data
–
it’s
not
rocket
science
CC BY!
81. Even
Instruc@onal
Tech
is
Guilty
You’ve
had
classes
on
designing
effec@ve
instruc@on
–
have
you
ever
had
a
class
on
designing
instruc@on
that
generates
the
right
kinds
of
data?
CC BY!
82. Even
Instruc@onal
Tech
is
Guilty
Have
you
ever
had
a
class
on
how
to
use
data
(in
real-‐@me
or
otherwise)
to
op@mize
your
instruc@on?
CC BY!
83. The
An@-‐Role
Replacing
all
human-‐to-‐human
interac@on
with
human-‐to-‐machine
interac@on
No
efficiency,
scale,
or
other
argument
jus@fies
taking
people
out
of
educa@on
CC BY!
84. If
Educa@on
Ignores
the
Trends…
The
“alterna@ves”
(protestants)
will
begin
springing
up
(e.g.,
charter
schools,
Phoenix,
Capella,
Walden,
Kaplan,
etc.)
CC BY!
85. Rather
than
a
30
Years
War…
You’re
going
to
end
up
reforming
anyway
-‐
why
not
do
it
on
your
own
terms,
before
ceding
leadership?
CC BY!
86. The
Reese’s
Cup
What
happens
when
you
put
the
“open”
chocolate
in
the
“data”
peanut
buWer?
CC BY!
92. If
the
research
on
the
2
sigma
problem
yields
prac@ced
methods
(methods
that
the
average
teacher
or
school
faculty
can
learn
in
a
brief
period
of
@me
and
use
with
li6le
more
cost
or
8me
than
conven@onal
instruc@on),
it
would
be
an
educa@onal
contribu8on
of
the
greatest
magnitude.
(p.
5)
Bloom,
1984
CC BY!
93. To
Tutor
Or
Not
to
Tutor?
That
is
the
(false)
ques@on
CC BY!
94. “Strategic
Tutoring”
What
if
we
could
do
just-‐in-‐@me,
just-‐on-‐topic,
one-‐on-‐one
tutoring?
CC BY!
95. Obs.
1
-‐
Requires
Great
Insight
We’d
have
to
know
who
needs
help,
when,
and
what
they
need
help
with
CC BY!
96. Obs.
2
-‐
Requires
Great
Curriculum
The
more
the
student
can
learn
from
the
materials,
the
less
tutoring
is
required
CC BY!
97. Obs.
3
-‐
Data
Is
the
Key
You’d
need
live,
fine-‐grained
data
about
student,
assessment,
and
curriculum
performance
CC BY!
98. Simultaneous
Con@nuous
Improvement
Working
in
a
way
that
constantly
improves
both
student
learning
and
the
curriculum
CC BY!
99. The
Loop
Curriculum
Redesign!
Data Data
Supporting Curriculum Describing
Strategic Use! Curriculum
Tutoring! Performance!
Student!
Performance!
Data!
CC BY!
100. OHSU
Teaching
Model
Create
and
aggregate
great,
open
curriculum,
let
it
do
as
much
instruc@ng
as
possible,
follow-‐up
with
“strategic
tutoring”
CC BY!
101. How
Do
You
Improve
Curriculum?
Performance
data
alone
aren’t
sufficient
–
you
need
permission
CC BY!
102. Open
Educa@onal
Resources
Give
OHSU
the
permissions
it
needs
to
engage
in
con@nuous
improvement
CC BY!