Data Collection:
An Introduction
PowerPoint Slides
to be used in conjunction
with the Facilitator’s Guide
Copyright © 2012, East Carolina University.
Recommended citation:
Wakeman, S., & Henderson, K. (2012). Data collection: An
introduction – A PowerPoint presentation for
professional development. Modules Addressing
Special Education and Teacher Education (MAST).
Greenville, NC: East Carolina University.
This resource includes contributions from the module
developer and MAST Module Project colleagues (in
alphabetical order) Kelly Henderson (Facilitator Guide
Editor), Tanner Jones (Web Designer), Diane Kester
(Editor), Sue Byrd Steinweg (Project Director), Bradley
Baggett (Graduate Assistant), and Sandra Hopfengardner
Warren (Principal Investigator).
Session Agenda
•
•
•
•
•
•
Introduction
Session Goals and Objectives
Background Overview
Legislation
Data Collection Design
Response Modes
Session Agenda, continued
•
•
•
•
•
•
Writing Measurable Skills/Tasks
Data Collection
Practice Matching Skill to Sheet
Reliable Data Collection
Summary
Evaluation
Introduction
Brian is a student in Mrs.
Stephens’ 7th grade class. He
works very hard and tries on
every task he is given. One
task in particular is troubling
for Mrs. Stephens. Brian
needs to work on solving for a
variable in an algebraic
equation.
Introduction, continued
He works on this task in his inclusion class
as well as on his homework, therefore Mrs.
Stephens rarely sees him solve a problem.
He can add and subtract with regrouping,
so Mrs. Stephens feels comfortable that he
can complete that part of the task. He
continues to get each question wrong,
however, and she is not sure what to do
about it.
Introduction, continued
• What ideas do you have to help her
gather information about Brian’s
performance?
• One way Mrs. Stephens could find out
what is happening within Brian’s
performance is to collect data during his
performance using a systematic method
or plan.
Introduction, continued
• Mrs. Stephens could:
– identify the steps to solve for the variable and
create a task analytic data collection sheet and
use it to gather data as she observes Brian
attempting to solve for the variable.
– Or Mrs. Stephens could analyze work samples
to identify error patterns by examining papers
from Brian on which he has worked out on
paper each step to solve the problem.
• Either approach would allow Mrs. Stephens
to collect performance data from Brian.
Introduction, continued
• Data could be collected by the teacher,
paraprofessional, general education
teacher, and/or parent using a specified
method. Whichever method, the data
collected should inform their
instructional efforts for supporting Brian.
Session Goal and Objectives
Objectives: Participants will be able to:
1. Identify types of data collection systems
with a focus on the data collection sheets
(e.g., task analysis, repeated trial, repeated
opportunity).
2. Identify measurable skills with a condition,
behavior, and criterion for mastery.
3. Identify the correct data collection sheet for
a given skill.
Overview
• Data collection is the objective and accurate
measurement of a student’s present level of
performance of and progress, or lack of
progress, on a task, activity, or behavior.
• Starting point- the baseline data of what the
student is currently doing or not doing.
• Data collection ends at the point where the
student reaches the criteria for mastery.
Overview, continued
• Accurate data collection allows the
teacher or service provider to determine:
(a) a student’s present levels of performance
(PLOP);
(b) any changes needed to provide
adaptations to the materials or the
interventions;
(c) student progress or lack of progress;
(d) program modifications or supports which
are necessary; and
(e) any patterns of behavior.
Overview, continued
• Data can be used on a:
– daily basis to inform instructional and
behavioral efforts for individual students.
– monthly, quarterly, or yearly basis to inform
programming efforts (e.g., the need for
additional or tertiary level interventions, the
need for support services, and the plan for
sequential instructional efforts).
Legislation
• The Individuals with Disabilities
Education Act (1997) required schools
to:
– monitor and provide parents with
documentation of a child’s progress towards
mastery for annual Individual Education
Program (IEP) goals and objectives; and
– provide documentation of special education
student participation in state-wide alternate
assessments.
Legislation, continued
• Data collection plays an essential part in
this documentation, particularly in states
that require teachers to provide evidence
of student work as a part of assessment.
• Data collection has been recognized as a
cornerstone for research-based practices.
For example, Response to Intervention
(RTI) is based upon the collection of valid
student performance data.
Data Collection Design
• Data collection of student progress is
designed to be:
– Objective: data should be measured
objectively. The skill must be observable and
measurable. It must be written in a manner
that enables multiple observers to see the
same outcome. The use of multiple observers
is an important step to demonstrate that the
data is a valid representation of the student’s
performance.
Data Collection Design, continued
– Systematic: the process of collecting data must
follow a systematic pattern. Random collection
of different expectations or outcomes creates
the chance of a variety of interpretations of the
data. Defining the cues, prompts (including
error corrections), materials, and data
collectors is necessary. A plan should be
identify when data collection should occur;
data would typically be taken at least 2-3 times
a week.
Data Collection Design, continued
– Defensible: a data collection system should
be carefully thought out. Why should the
teacher collect this data and collect it this
way? Data provides teachers with the
necessary information to make defensible
decisions about instruction.
Response Modes
• Data collected must be an accurate
representation of what the student knows
and can do.
• Tasks must be designed and supports
must be utilized in such a way as the
student can independently respond to any
items presented.
Response Modes, continued
– For example, if a task was defined for a
student to identify sight words but the student
used picture symbols and photographs for
receptive and expressive language, the task
would be too difficult for the student.
– However, if the student was asked to increase
his picture vocabulary paired with the written
word, the student could respond within the task
as designed. How the student responds best
must be considered when designing a task in
which data will be collected.
Response Modes, Activity ?
– Review sample data sheets. Examine
the objective for each data sheet to
see (a) what responses students
would have to have to be able to
show their understanding of the task
as well as (b) what supports are
provided to them to make an accurate
response possible.
Response Modes, continued
• Designing the system to collect data
typically falls to the teacher or behavior
specialist. These practitioners are
responsible for:
(a) identifying and defining skill/behavior;
(b) establishing the baseline performance of the
student (what the student can do) and the
criteria, including mastery (what they want the
student to be able to do);
(c) creating a user-friendly data collection
method;
Response Modes, continued
(d) training team members to collect data across
environments;
(e) reviewing and analyzing data weekly; and
(f) modifying programs based on data.
• The skill or target behavior is typically an
IEP objective, a skill related to prioritized
content standards, a behavior that impedes
the student’s learning, or a skill to be
assessed for a formal assessment, such as
the alternate assessment.
Writing Measurable Skills/Tasks
• There are three components to each
skill or task: condition, behavior, and
mastery level.
• The following narrated slides are
available at
http://mast.ecu.edu/modules/dc_intro/lib
/media/slides01/SlideShow.html.
Writing Measurable
Skills/Tasks
Data Collection: An Introduction
Condition
• What will be
presented to the
student?
• What materials
will be used (be
generic)?
• Given manipulatives, a
worksheet with 10
problems, and
scaffolded support, if
necessary, and a
pencil, Josh will
independently solve 9
out of the 10 problems
correctly for 3
consecutive trials.
Behavior
• Given manipulatives,
• What will the
a worksheet with 10
student be doing?
problems and
scaffolded support, if
necessary, and a
pencil, Josh will
independently solve 9
out of the 10
problems correctly for
3 consecutive trials.
Criteria for Mastery
• What level of
•
increase or
accuracy are you
expecting?
• How many days will
the student have to
reach that criteria
to be considered as
having mastered
the task?
Given manipulatives, a
worksheet with 10
problems and scaffolded
support, if necessary,
and a pencil, Josh will
independently solve 9
out of the 10 problems
correctly for 3
consecutive trials.
What is missing?
• Jane will independently read 4 out of 5
sight words correctly for 3 consecutive
trials.
• Given a writing instrument or stamper,
Michael will independently mark on paper
as an emerging signature.
• Given her phone number and a
distractor, Gerry will independently point
to her own phone number 4 of 5 trials
correctly for 3 out of 5 days.
Non Examples
• What is wrong with the way the
following tasks are written?
– Sherrie will participate in an inquiry
based science lesson with physical
assistance for 4/5 trials.
– Given a book of her choice, Lynn will
read a book independently.
– Given a crosswalk sign, Joel will
cross the street safely on 8 of 10
occasions.
Activity suggestion
- What unusual experiences have you had
with writing measurable skills and
objectives and the results?
Data Collection
• Creating a user-friendly data collection
method starts with the skill or task and
deciding how to document progress. Options
include data sheets, permanent products
(e.g., work samples), anecdotal notes, or a
combination.
• Data collection sheets should be determined
prior to instruction or assessment. Selection
is guided by the purpose the data and the
way the task is written.
Data Collection, continued
• Some examples of different types of data
collection sheets follow.
a) Task Analysis- Outlines the steps
necessary to complete a task. When the
student is presented the task to complete,
the number of steps correct is scored. The
teacher decides on the number of steps
presented in each trial (total task versus
forward or backward chaining).
Data Collection, continued
• For example, a task analysis data sheet
would likely be used to record the steps for
a student to use money in a vending
machine or the steps in a science
experiment.
• An example of a task analytic data sheet
follows and is available at
http://mast.ecu.edu/modules/dc_intro/lib/do
cuments/Task_Analysis_Data_Sheet.pdf .
Data Collection, continued
b) Repeated Trial- One of the most common
data sheets. Teacher delivers teaching
trials in a set (e.g., present a sight word,
then another word, then another word, etc.)
Responses given by student are charted on
the data sheet (either correct/incorrect or
independent/prompted depending upon if
the task is instructional or assessment
Data Collection, continued
• An example of a repeated trial data sheet
is provided here. A copy of the repeated
Trial Data Sheet follows and is available
at
http://mast.ecu.edu/modules/dc_intro/lib/d
ocuments/Repeated_trial_data_sheet.pdf.
Data Collection, continued
• Note on the data sheet that items
presented to the student are listed on the
left side of the data sheet and each unique
item has its own row for data collection.
• It’s easy to see if a pattern emerges for
specific items (e.g., the student can
identify snowy consistently but not cloudy).
Data Collection, continued
• This is important as specific items may
be too difficult for the student and
prevent mastery of the overall task
• For example- the task is 8 out of 10 sight
words and the student consistently gets
7 correct, the teacher can decide what
instructionally to do next to support
student acquisition of the 3 words that
are preventing mastery of the task.
Data Collection, continued
c) Repeated Opportunity- appropriate for
skills that are taught throughout day,
i.e., the trials are spread out. The
student’s responses are charted as they
are made. Examples of skills that could
be recorded on a repeated opportunity
data sheet are using an object schedule
or telling clock time at start of each
lesson.
Data Collection, continued
• An example of a Repeated Opportunity
Data Sheet with data in it follows and is
available at
http://mast.ecu.edu/modules/dc_intro/lib
/documents/Repeated_Opportunity_dat
a_sheet.pdf.
Data Collection, continued
• On the previous data sheet, the who,
where, and potentially with what the
student makes the response for the task
or item is recorded for each opportunity.
• In this case, the student is learning to
independently transition when given a
prompt during different parts of his
schedule.
Data Collection, continued
• Some students may respond differently to
different people or in different locations
depending upon what distractors may be
present.
• This type of repeated opportunity data
allows the teacher to see what patterns, if
any, exist that prevent or promote the
students response.
Data Collection, continued
d) Frequency- typically used to measure
the degree to which there is an increase
or decrease in number of times the
student uses a new response or refrains
from an unwanted response. This skill
or task may be measured throughout
day (e.g., hand raising instead of calling
out) or in one lesson (e.g., activating a
communication device to respond).
Data Collection, continued
• An example of a frequency data sheet
follows and is available at
http://mast.ecu.edu/modules/dc_intro/lib
/documents/Frequency_data_sheet.pdf.
Data Collection, continued
• The previous sheets is an example of
how frequency data can be taken. The
student is sorting a series of pictures into
two categories. The frequency of how
many pictures were sorted correctly is
recorded.
• Another example of how frequency data
could be collected is to simply record a
number for each date the items or prompt
is given.
Data Collection, continued
• For example, students could record how
many sit ups they do each day, the
number of correct math facts in a minute,
or the number of out of seat occurrences
in a class period. A simple table can
include date and number of responses.
Date
Response
3/16/10
14
3/17/10
16
3/18/10
18
Data Collection, continued
e) Duration- used to record a skill that is
measured in time, specifically, the total
amount of time the student engages in
task. The purpose of the instruction may
be to increase the amount of time (e.g.,
attending to task) or decrease the
amount of time (e.g., length of
tantruming behavior). Time could be
recorded in seconds or minutes.
Data Collection, continued
• A duration data sheet may be appropriate
when the student is expected to work for
30 consecutive minutes on a vocational
task or to indicate the length of time for a
student to transition between tasks.
• An example of a duration data sheet with
data follows and is available at
http://mast.ecu.edu/modules/dc_intro/lib/d
ocuments/Duration_data_sheet.pdf.
Data Collection, continued
• This duration data sheet has four
columns, but a sheet could have an
additional column in which the prompting
level (i.e., physical, model, or
independent) is listed on its own.
• In the example, mastery was described
in the objective as an independent
performance of the task under 30
seconds of the given prompt for 3
consecutive days.
Data Collection, continued
• It is possible that the time may also be
increased (e.g., actively engaged in
completing a given task by 10 seconds
each day until student completes a
given task without prompting up to 5
minutes).
Data Collection, continued
f) Cumulative- appropriate when one
discrete response is to be used
throughout the day or over a period of
days. Responses are totaled over days
to reach a criterion. An example of a
skill for which a teacher may use a
cumulative data sheet is when a student
is expected to independently ask for
help when appropriate.
Data Collection, continued
• An example of a cumulative data sheet
with data follows and is available at
http://mast.ecu.edu/modules/dc_intro/lib
/documents/Cumulative_data_sheet.pdf
.
Data Collection, continued
• Notice the objective on the previous data
sheet. The expectation for mastery is
such that the student will acquire a set of
information over a longer period of time
rather than within a given response set
(like the repeated trial data sheet).
• The student is to independently
recognize 10 new science terms within
context over the school year.
Data Collection, continued
• Student responses are considered in the
context of natural cues or when the
chance is given to elicit the response
that may not occur on a daily or even
weekly basis.
Data Collection, continued
• One important consideration when
designing a data sheet is to first
determine the purpose for collecting the
data.
– Is the data collected being used for
assessment purposes or is it being used
within instructional trials?
Data Collection, continued
• The video included later is an
assessment. When presenting
assessment trials, the teacher will
typically not provide correct responses
unless the student replies, “I don’t know”
as instructed prior to the beginning of
the assessment.
Data Collection, continued
• If it was an instructional video rather than
an assessment video, the teacher would
correct errors and support student
acquisition of the words within each trial,
likely using a prompting system. Note the
difference when you watch the video.
• The table that follows helps illustrate the
type of scoring that would occur
depending upon the purpose or use of the
data.
Data Collection, continued
• For an assessment probe (a set of items
presented to test what the student knows
and can do independently) the first row
shows what would be recorded on the data
sheet- accuracy of responses.
• The repeated trial data sheet in this module
is an example of an assessment probe.
Data Collection, continued
• For an instructional probe, typically the
data sheet will list a prompting system
in the key. The duration data sheet in
this module is an example of an
instructional probe.
Data Collection, continued
Response is
correct/incorrect
(ASSESSMENT OR NON
INSTRUCTIONAL)
Type of prompt or
highest level of prompt
used
+ = Correct
– = Not correct
x = Does not attempt
I = Independent
G = Gestural
NV = Non-Specific Verbal (e.g.,
“What’s next?”)
V = Verbal
M = Model
P = Partial Physical
F = Full Physical
Practice Matching Skill to Sheet
• Watch the slide show at
http://mast.ecu.edu/modules/dc_intro/lib
/media/slides02/SlideShow.html to
practice matching skills to the correct
data sheet. Copies of the slides follow.
Matching skills to data sheets
• Data collection: An Introduction
Which is this?
Student:
Steps:
Task: Given a computer and website, Student
will complete all steps to locate chosen website
independently at 100% accuracy for 3 websites.
Dates:
1. Find and double-click
Internet Explorer icon
2. Wait for Home page to
appear
3. Find and click “Search” icon
in toolbar
4. Type in search topic of
choice
5. Find and click “Search”
button
6. Click desired web page
Total Independent Correct:
Where:
With Whom:
9/02
9/07
9/09
9/12
9/16
9/18
9/20
I
I
I
I
I
I
I
V
V
V
V
I
I
V
M
M
V
V
M
M
V
V
V
V
V
V
V
V
M
I
2
CL
T
I
V
2
H
PA
I
M
2
MC
T
M
M
1
CC
CTS
M
V
2
CL
A
M
V
2
CC
CTS
I
I
3
H
PA
And this?
Student:
Date
10/01
10/02
10/06
10/09
10/10
Task: When given a book on tape and switch,
student will activate the switch to start the book
in less than 30 seconds for 3 consecutive trials.
Student Response/Time
on Task
M/65 secs.
M/62 secs.
M/60 secs.
P/59secs.
P/60 secs.
Where
CL
LG
CL
LG
CL
With Whom
T
A
T
P
A
And this?
Task: Given sight words written on index cards, Student will identify 5 out
of 7 weather related words for 3/5 trials.
Student:
Date:
1 Snowy
2 Cloudy
3 Sunny
4 Rainy
5 Windy
6 Hot
7 Cold
Where:
With:
Material Used:
Total Independent
Correct:
3/03
+
+
+
+
+
+
H
PA
HWK
6
3/04
+
+
+
+
+
MC
A
N
5
3/07
+
+
+
+
+
+
CL
T
W
6
3/10
+
+
+
+
+
+
CL
P
W
6
3/12
+
+
+
+
+
H
PA
HWK
5
3/13
+
+
+
+
+
CL
T
W
5
3/18
+
+
+
+
+
+
MC
A
N
6
3/20
+
+
+
+
+
H
PA
HWK
5
3/21
+
+
+
+
+
CL
P
W
5
3/25
+
+
+
+
+
+
MC
A
N
6
3/26
+
+
+
+
+
+
H
PA
HWK
6
How about this one?
Student:
Date:
1
2
3
4
5
Where:
With:
Material Used:
Total Independent
Correct:
Task: Given her AAC device and a story, Student will activate a voice
output device to indicate a repeated story line 4/5 times requested for 3
stories.
3/03
+
+
+
+
3/04
+
+
+
-
3/07
+
+
+
+
3/10
+
+
+
+
-
3/12
+
+
+
-
3/13
+
+
+
-
3/18
+
+
+
+
-
3/20
+
+
+
3/21
+
+
+
-
3/25
+
+
+
+
3/26
+
+
+
+
+
H
PA
HWK
MC
A
N
CL
T
W
CL
P
W
H
PA
HWK
CL
T
W
MC
A
N
H
PA
HWK
CL
P
W
MC
A
N
H
PA
HWK
4
3
4
4
3
3
4
3
3
4
5
What about this one?
DATE
Given a reminder card on his
desk, Marcus will get out of his
seat less than three times a day
without asking for 5 consecutive
days.
4/11
llll=4
4/12
lllllllll=9
4/15
lll=3
4/16
lll=3
4/17
lll=3
How about which sheet would you
use for these skills?
• Given a jig and materials, Matt will set the
table correctly (follow 5 steps) each day
for 3/5 days.
• Given 15 minutes of leisure time, Jerry will
stay in the leisure area leaving no more
than once without asking for 5 trials.
• Given familiar people, Kitty will initiate a
greeting as she approaches for 3 or more
people each day.
Reliable Data Collection
• One important aspect of data collection is
ensuring that the data collected is
objective:
– Some measures in place to avoid biased or
incorrect data being included in the data set.
– Biased data is not objective.
– Data collectors who have preconceived
ideas about how the data should be may not
be able to see what is actually happening,
particularly in behavioral issues. here.
Reliable Data Collection, continued
– Incorrect data can happen when the person
collecting data does not recognize the prompt
or does not understand what a correct
response looks like for the student.
– Data should be apparent and available to
stakeholders.
– The data should be defensible in its accuracy
and should be a valid representation of what
the student is actually doing as it plays a key
role in making decisions about the student’s
education.
•
Reliable Data Collection, continued
• Watch the video at
http://mast.ecu.edu/modules/dc_intro/lib/
media/MOV051.html. The video
illustrates a child reading sight words:
Galaxy, Saturn, Jupiter, Earth, Venus,
Mars, Mercury, Uranus, Pluto, Neptune.
• Use a repeated trial data sheet and take
data with the assessor.
Reliable Data Collection, continued
• After completing your own data
collection, view the answers in the data
sheet available at
http://mast.ecu.edu/modules/dc_intro/lib/
documents/Data_Sheet_answers_solar_
system_sight_words_data_collection.pdf
once you have watched the video. A
copy of the data sheet follows.
Reliable Data Collection, continued
• Check your answers with the answer sheet
provided. A few of the incorrect responses
are worth discussion:
– Emma mispronounces Uranus in trial two so it
is first checked by the teacher and then
recorded as an incorrect response.
– Emma also says in trial 2 that she does not
know a word (Mercury), so that word is also
marked as incorrect.
Reliable Data Collection, continued
– When reviewing the mastery level set in
the objective for the task, Emma does not
master this task as she was required to get
9 out of 10 correct for three consecutive
trials and Emma only has one trial at the
mastery level.
Summary
• Data collection is one of the most important
aspects of instruction and assessment.
• If a plan to collect observable, measurable,
valid data is in place, practitioners can
identify student response patterns and
support student progress towards mastery.
• Skills or tasks must be written with a
condition, behavior, and criteria for mastery.
Summary, continued
• Data collection systems can include
student work samples, anecdotal records,
data sheets, or a combination of all three.
• Data can be collected using a data sheet
that best matches the purpose or use of
the data and the type of skill to be
measured.
Summary, continued
• Examples of data sheets include task
analytic, repeated trial, repeated
opportunity, frequency, duration, and
cumulative.
• Finally, reliable data collection is a must
before analysis of the data can occur.
Focus and Reflection Questions
• What do you think is the most
difficult part of creating and using
data collection strategies?
• Why?
• What can you suggest to make the
task easier?
Application and Extension
Activities
1. Data can be collected using a data
sheet that best matches the purpose or
use of the data and the type of skill to
be measured. Examples of data sheets
include task analytic, repeated trial,
repeated opportunity, frequency,
duration, and cumulative.
Application and Extension
Activities, continued
Design their own data sheets for specific
purposes and types of skills for other tasks
and/or objectives, keeping in mind your
classroom and students.
• Frequency
• Task analytic
• Repeated trial
• Duration
• Repeated opportunity • Cumulative
Self-Assessment
• A self-assessment with response feedback
is available at
http://mast.ecu.edu/modules/dc_intro/quiz/
. Participants may take this assessment
online to evaluate their learning about
content presented in this module.
Session Evaluation
• A form for participants to evaluate the
session is available in the Facilitator’s
Guide.
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