Whether our special education students are learning in self contained or inclusion classrooms, maintaining high quality standardized data collection practices is critical to tracking, monitoring, and conveying student progress. Collecting data not only demonstrates and reinforces student learning, but also informs instruction and supports teachers in being reflective about their own practice. Yet as students move into inclusion settings, and teachers become responsible not only for teaching more students, but sometimes for addressing a wider variety of needs, finding ways to collect and monitor student data can become more challenging. In this webinar Rethink’s Angela Pagliaro discusses strategies for integrating data collection into diverse settings, particularly inclusion classrooms.

1.
Differen(a(ng
Data
Collec(on:
Best
Prac(ce
Tips
for
Collec(ng
Data
in
Inclusive
Se;ngs
Presented
by
Angela
Pagliaro,
MA,
BCBA

2.
Par(cipants
Will
Learn:
1. How
to
collect
norma/ve
data
in
inclusive
se5ngs
2. How
to
set
meaningful
goals
for
student
in
inclusion
se5ngs
3. Sugges/ons
for
types
of
data
to
collect
according
to
se5ng

3.
How
Do
We
Support
Students
in
Inclusive
Se;ngs?
1. Assess
Student
for
Readiness
– Conduct
Inclusion
Assessment
– VB-­‐MAPP
Transi/on
Assessment
– AFLS
(Assessment
of
Func/onal
Living
Skills)

4. 2.
Iden(fy
Goals
Based
Upon
Assessment
Results
– Take
Norma/ve
Data
– Teach
Pre-­‐requisite
skills
if
necessary
How
Do
We
Support
Students
in
Inclusive
Se;ngs?

5. 3.
Iden(fy
Appropriate
Inclusion
Se;ng
– Educate
Inclusion
Se5ng
Staff/Employees
of
Student’s
Goals
– Review
what
their
role
is
in
the
inclusion
opportunity
for
student
How
Do
We
Support
Students
in
Inclusive
Se;ngs?

6. 4.
Iden/fy
Who
is
Responsible
for
Collec/ng
Data
and
What
kind
of
data
will
be
Collected
How
Do
We
Support
Students
in
Inclusive
Se;ngs?

7.
What
Se;ngs
Are
We
Talking
About?
General
Educa(on
Se;ng
– Elementary
– Middle/High
School
Voca(onal
Se;ng
– Job
Coaching
Sites

8.
What
is
Norma(ve
Data
and
Why
do
We
Need
It?
Norma&ve
data
is
data
that
is
collected
from
age-­‐matched
peers
in
the
same
or
similar
se3ng
that
has
been
iden5fied
as
an
inclusion
opportunity
for
your
student.
Norma5ve
data
will
help
you
set
up
expecta5ons
and
goals
for
the
student
that
you
are
suppor5ng
for
the
inclusion
se3ng.

9. Educa(onal
Inclusion
Opportuni(es

10.
Examples
of
Norma(ve
Data
to
Collect
for
the
Elementary
Educa(onal
Se;ng:
1. How
many
/mes
does
peer
raise
hand
in
circle?
2. How
long
do
peers
sit
in
circle
/me/lesson
before
ge5ng
antsy?
3. How
many
/mes
does
peer
respond
with
the
group?
4. How
many
/mes
does
peer
respond
to
another
peer?
5. How
many
/mes
does
a
peer
ini/ate
conversa/on
and/or
answer
ques/ons?
6. How
long
does
it
take
peer
to
complete
assignments?

11.
Poten(al
Goals
for
Elementary
Inclusion
Opportuni(es:
1. Raising
hand
to
answer
ques/ons
in
circle
2. Si5ng
in
circle
for
longer
dura/ons
3. Responding
along
with
a
group
4. Responding
to
peers
ques/ons
and
comments
5. Making
play
related
comments
6. Comple/ng
assignments
independently

12.
What
Type
of
Data
to
Collect
for
Elementary
School
Inclusion
Se;ng:
1. Frequency
Data:
– Collect
the
number
of
/mes
behavior
occurs
(e.g.,
raises
hand,
responds
along
with
group,
makes
comment
to
peer)
2. Par(al
Interval
Data:
– Collect
if
the
behavior
occurred
or
did
not
occur
in
a
specific
/me
interval
3. Dura(on:
– Collect
total
/me
behavior
occurred
(e.g.,
/me
student
sat
in
circle,
remained
on
task,
par/cipated
in
non-­‐preferred
ac/vity)

16.
Middle/High
School

17.
Example
Norma(ve
Data
to
Collect
for
the
Middle/High
School
Se;ng:
1. How
long
does
it
take
peer
to
transi/on
between
classes?
2. How
many
mul/-­‐step
instruc/ons
are
given
in
a
classroom?
3. How
long
to
students
give
presenta/ons
for?
4. How
many
tasks
do
students
engage
in
during
group
work?
5. How
many
conversa/onal
exchanges
occur
during
social
/me
(e.g.,
lunch
break)?
6. How
long
do
peers
stay
on
topic
during
conversa/ons?

18.
Poten(al
Goals
for
Middle/High
School
Inclusion
Opportuni(es:
1. Following
a
Schedule
(classroom
and
full
day
schedules)
2. Par/cipa/ng
in
group
work
(e.g.,
following
mul/-­‐step
instruc/ons,
giving
presenta/ons,
working
in
a
group)
3. Engaging
in
Study
Skills
(e.g.,
comple/ng
classwork,
following
along
with
a
lesson,
keeping
organized,
taking
notes
during
a
lesson,
raising
hand
to
ask
for
help)
4. Social
Skills
(e.g.,
Maintaining
a
conversa/on
about
a
topic,
maintaining
an
appropriate
distance,
self-­‐
monitoring,
demonstra/ng
asser/veness,
taking
turns)

19.
What
Type
of
Data
to
Collect
for
Middle/High
School
Inclusion
Se;ng:
1. Frequency:
– E.g.,
Number
of
assignments
completed,
number
of
/mes
arriving
to
class
on
/me,
2. Dura(on:
– E.g.,
Time
it
takes
to
transi/on
from
one
class
to
another
3. Interval
Recording:
– E.g.,
on
task
behavior,
following
classroom
rou/nes
4. Task
Analysis:
– For
long
response
chains
(e.g.,
comple/ng
a
schedule,
following
classroom
rou/nes)
.

21.
Self-­‐Monitoring

22.
Voca(onal
Se;ng

23.
Example
Norma(ve
Data
to
Collect
for
the
Voca(onal
Se;ng:
1. How
long
does
it
take
peer(s)
to
complete
voca/onal
related
tasks.
2. How
many
steps
of
a
work
task
can
peer
complete
in
given
amount
of
/me.
3. How
many
social
interac/ons
do
peers
engage
in
in
specified
voca/onal
se5ng?

24.
Poten(al
Goals
for
Voca(onal
Inclusion
Opportuni(es:
1. Following
a
schedule
(e.g.,
specific
to
the
voca/onal
site)
2. Task
related
skills
(e.g.,
cleaning
specified
areas,
making
change
using
a
cash
register,
sor/ng
items
for
recycling,
reading
and
following
direc/ons,
following
a
recipe,
stocking
shelves,
etc.)
3. Social
Skills:
(e.g.,
engaging
in
conversa/on
about
a
topic,
maintaining
personal
space,
accep/ng
feedback
and
correc/on,
calling
if
running
late)

25.
What
Type
of
Data
to
Collect
for
Voca(onal
Se;ng:
1. Task
Analysis
– E.g.,
for
long
response
chains
like
following
a
recipe,
cleaning
specified
areas,
sor/ng
items)
2. Group
Data
Collec(on
– E.g.,
ability
to
collect
data
for
mul/ple
students
in
voca/onal
se5ng
3. Frequency
– E.g.,
number
of
/mes
student
completes
task

28.
Tips
for
Data
Collec(on:
• Iden(fy
the
type
of
data
that
makes
most
sense
for
the
se5ng
and
student
goal
• When
in
the
community,
try
to
use
technology
to
collect
data
• Communicate
regarding
who
needs
to
be
collec/ng
the
data
• Collect
data
at
least
1
(me
per
week

29.
Ques(ons?

30. Thank
you.
Angela
Pagliaro,
MA,
BCBA
Angela.pagliaro@rethinkfirst.com