SlideShare ist ein Scribd-Unternehmen logo
1 von 21
Sponsored by FDLRS Action Resource Center
   Assessment
   Measurement
   Legal Accountability
   Collaboration
   Documentation
   Problem Solving
   Monitoring
   Provide Feedback

                           Diana Ferreira, Amy Rowe and
                           Ann Cacciatore, OCPS
   Factual and unbiased information

   Information is used for both academic and
    behavioral programming

   2 critical components to data collection
     Information gathering
     Decision making
• Problem                            Define
  Solving/RtI                                     What is the problem?
                  Is it working?
• CPI
COPING
  Model
                                    Academic
• Data-based
                       Evaluate        &         Analyze
  Decision                          Behavioral
  Making
  Model
                                                   Why is it occurring?
• Continuous    What intervention
                am I going to do?   Implement
Improvement
  Model
SUBJECTIVE (UN-
                                   OBJECTIVE (MEASURABLE)
        MEASURABLE)

   Logan throws a tantrum         Logan cries and kicks
    when he does not get his        objects/people when he
    way.                            is denied access to the
                                    computer.
   Angelina will identify         When given a verbal
    numbers.                        prompt “touch the
                                    number ___”, Angelina
                                    will expressively identify
                                    the requested number
                                    given an array of 3
                                    choices.
   Is objective and non-judgmental
   Helps to define the problem
   Original data (before any intervention has
    taken place)
   Is used to compare and evaluate the
    effectiveness of the intervention
Event Recording / Frequency   Record how many times a behavior occurs                Green



Duration                      Used to document the amount of time a student          Blue
                              spends in engaging in a behavior


A-B-C                         Antecedent – Behavior – Consequence                    Purple
                              Documents what occurs before/after a behavior


Percent Correct               Number of correct responses divided by the total       Pink
                              number of opportunities to respond


Latency                       Documents how long it takes for a behavior begin       Orange
                              after a demand or event occurs


                                                                        Diana Ferreira, Amy Rowe
                                                                        and
   Be consistent in the type of data
    collected

   Ensure that all who are taking data
    have been trained and understand
    the data collection tool being used.

   Does intervention/data collection
    plan pass the “Stranger Test”?
Meet Julie
What system(s) do
you have in place
for managing the
sometimes
overwhelming
amount of student
data that is
collected?
   Must occur to be able to analyze the
    data collected
   Quick and easy visual summaries that
    allow for easy determination of
     patterns of behavior
     evaluate results on new teaching strategies
     determine if interventions are/are not having
     the desired effects
   Review data points every 3 sessions

   Ask yourself is the data…
     Improving?
     Staying the same (flattening)?
     Worsening?


   Make a decision!
Possible Actions:
  Continue services and supports with current annual goal.
  Continue services and supports and increase annual goal.
  Gradually fade services or supports to determine if the student
    can perform independently.
                                                                     19
Possible Actions:
Determine if the services and supports were implemented as
intended.
  If not, improve implementation of services and supports.
  If yes, increase intensity of current services and supports and
     assess impact. If rate doesn’t improve, return to problem
                                                                     20
     solving.
Possible Actions:
Determine if the services and supports were implemented as
intended.
  If not, improve implementation of services and supports.
  If yes, return to problem solving.

                                                              21

Weitere ähnliche Inhalte

Ähnlich wie Data collection

Engagement to action / Ymgysylltu i weithredu
Engagement to action / Ymgysylltu i weithreduEngagement to action / Ymgysylltu i weithredu
Engagement to action / Ymgysylltu i weithreduParticipation Cymru
 
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....CORE Group
 
Assessment+and+intervention
Assessment+and+interventionAssessment+and+intervention
Assessment+and+interventioncayce_mccamish
 
Using Your Data: Which, When and How? Mo SW-PBS SI 2008
Using Your Data: Which, When and How? Mo SW-PBS SI 2008Using Your Data: Which, When and How? Mo SW-PBS SI 2008
Using Your Data: Which, When and How? Mo SW-PBS SI 2008Nanci Johnson
 
Data collection resource
Data collection resourceData collection resource
Data collection resourceRichard Haase
 
FIGURE 1SUMMARY INFORMATION1. Discuss the overall purpose of this.docx
FIGURE 1SUMMARY INFORMATION1.  Discuss the overall purpose of this.docxFIGURE 1SUMMARY INFORMATION1.  Discuss the overall purpose of this.docx
FIGURE 1SUMMARY INFORMATION1. Discuss the overall purpose of this.docxssuser454af01
 
Fba and fa powerpoint
Fba and fa powerpointFba and fa powerpoint
Fba and fa powerpointjmcullenbsu
 
Learning Analytics Primer: Getting Started with Learning and Performance Anal...
Learning Analytics Primer: Getting Started with Learning and Performance Anal...Learning Analytics Primer: Getting Started with Learning and Performance Anal...
Learning Analytics Primer: Getting Started with Learning and Performance Anal...Watershed
 
You Want Me to Measure What?
You Want Me to Measure What?You Want Me to Measure What?
You Want Me to Measure What?Dave Hogue
 
Key Notes Slides
Key Notes SlidesKey Notes Slides
Key Notes SlidesBeth Kanter
 
Results Based Accountabillty
Results Based AccountabilltyResults Based Accountabillty
Results Based AccountabilltySuncoastMeetings
 
In Chuck Norris we trust - A3 thinking intro
In Chuck Norris we trust - A3 thinking introIn Chuck Norris we trust - A3 thinking intro
In Chuck Norris we trust - A3 thinking introHanno Jarvet
 
G-51-Collecting-Effective-Data-in-Counseling.pptx
G-51-Collecting-Effective-Data-in-Counseling.pptxG-51-Collecting-Effective-Data-in-Counseling.pptx
G-51-Collecting-Effective-Data-in-Counseling.pptxsudhashinithiruchelv
 
Machine learning meets user analytics - Metageni tech talk
Machine learning meets user analytics - Metageni tech talkMachine learning meets user analytics - Metageni tech talk
Machine learning meets user analytics - Metageni tech talkGabriel Hughes PhD
 
Agile camp 2018 - Team Metrics
Agile camp 2018 - Team MetricsAgile camp 2018 - Team Metrics
Agile camp 2018 - Team MetricsTheAgileDen
 

Ähnlich wie Data collection (20)

Engagement to action / Ymgysylltu i weithredu
Engagement to action / Ymgysylltu i weithreduEngagement to action / Ymgysylltu i weithredu
Engagement to action / Ymgysylltu i weithredu
 
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....
Seven steps for Use Routine Information to Improve HIV/AIDS Program_Snyder_5....
 
Assessment+and+intervention
Assessment+and+interventionAssessment+and+intervention
Assessment+and+intervention
 
Using Your Data: Which, When and How? Mo SW-PBS SI 2008
Using Your Data: Which, When and How? Mo SW-PBS SI 2008Using Your Data: Which, When and How? Mo SW-PBS SI 2008
Using Your Data: Which, When and How? Mo SW-PBS SI 2008
 
Data collection resource
Data collection resourceData collection resource
Data collection resource
 
FIGURE 1SUMMARY INFORMATION1. Discuss the overall purpose of this.docx
FIGURE 1SUMMARY INFORMATION1.  Discuss the overall purpose of this.docxFIGURE 1SUMMARY INFORMATION1.  Discuss the overall purpose of this.docx
FIGURE 1SUMMARY INFORMATION1. Discuss the overall purpose of this.docx
 
Fba and fa powerpoint
Fba and fa powerpointFba and fa powerpoint
Fba and fa powerpoint
 
Learning Analytics Primer: Getting Started with Learning and Performance Anal...
Learning Analytics Primer: Getting Started with Learning and Performance Anal...Learning Analytics Primer: Getting Started with Learning and Performance Anal...
Learning Analytics Primer: Getting Started with Learning and Performance Anal...
 
Conniechp5
Conniechp5Conniechp5
Conniechp5
 
You Want Me to Measure What?
You Want Me to Measure What?You Want Me to Measure What?
You Want Me to Measure What?
 
Key Notes Slides
Key Notes SlidesKey Notes Slides
Key Notes Slides
 
Results Based Accountabillty
Results Based AccountabilltyResults Based Accountabillty
Results Based Accountabillty
 
In Chuck Norris we trust - A3 thinking intro
In Chuck Norris we trust - A3 thinking introIn Chuck Norris we trust - A3 thinking intro
In Chuck Norris we trust - A3 thinking intro
 
Conniechp5v10
Conniechp5v10Conniechp5v10
Conniechp5v10
 
Techniques
TechniquesTechniques
Techniques
 
APIP Book Talk
APIP Book TalkAPIP Book Talk
APIP Book Talk
 
G-51-Collecting-Effective-Data-in-Counseling.pptx
G-51-Collecting-Effective-Data-in-Counseling.pptxG-51-Collecting-Effective-Data-in-Counseling.pptx
G-51-Collecting-Effective-Data-in-Counseling.pptx
 
Machine learning meets user analytics - Metageni tech talk
Machine learning meets user analytics - Metageni tech talkMachine learning meets user analytics - Metageni tech talk
Machine learning meets user analytics - Metageni tech talk
 
Agile camp 2018 - Team Metrics
Agile camp 2018 - Team MetricsAgile camp 2018 - Team Metrics
Agile camp 2018 - Team Metrics
 
Poster
PosterPoster
Poster
 

Mehr von FDLRS

Visual supports
Visual supportsVisual supports
Visual supportsFDLRS
 
Student profile
Student profileStudent profile
Student profileFDLRS
 
Physical structure
Physical structurePhysical structure
Physical structureFDLRS
 
Communication
CommunicationCommunication
CommunicationFDLRS
 
Meaningful work
Meaningful workMeaningful work
Meaningful workFDLRS
 
Collaboration
CollaborationCollaboration
CollaborationFDLRS
 
Classroom Scheduling
Classroom SchedulingClassroom Scheduling
Classroom SchedulingFDLRS
 
Student Schedules
Student SchedulesStudent Schedules
Student SchedulesFDLRS
 
Instructional Practices
Instructional PracticesInstructional Practices
Instructional PracticesFDLRS
 
Social Skills
Social SkillsSocial Skills
Social SkillsFDLRS
 
Student Profile
Student ProfileStudent Profile
Student ProfileFDLRS
 
Physical Structure
Physical StructurePhysical Structure
Physical StructureFDLRS
 
Communication
CommunicationCommunication
CommunicationFDLRS
 
Behavior
BehaviorBehavior
BehaviorFDLRS
 
Visual Supports
Visual SupportsVisual Supports
Visual SupportsFDLRS
 
BLTA Orientation
BLTA OrientationBLTA Orientation
BLTA OrientationFDLRS
 
Session 3
Session 3Session 3
Session 3FDLRS
 

Mehr von FDLRS (18)

Visual supports
Visual supportsVisual supports
Visual supports
 
Student profile
Student profileStudent profile
Student profile
 
Physical structure
Physical structurePhysical structure
Physical structure
 
Communication
CommunicationCommunication
Communication
 
Meaningful work
Meaningful workMeaningful work
Meaningful work
 
Collaboration
CollaborationCollaboration
Collaboration
 
Classroom Scheduling
Classroom SchedulingClassroom Scheduling
Classroom Scheduling
 
Student Schedules
Student SchedulesStudent Schedules
Student Schedules
 
Instructional Practices
Instructional PracticesInstructional Practices
Instructional Practices
 
Social Skills
Social SkillsSocial Skills
Social Skills
 
Student Profile
Student ProfileStudent Profile
Student Profile
 
RtI
RtIRtI
RtI
 
Physical Structure
Physical StructurePhysical Structure
Physical Structure
 
Communication
CommunicationCommunication
Communication
 
Behavior
BehaviorBehavior
Behavior
 
Visual Supports
Visual SupportsVisual Supports
Visual Supports
 
BLTA Orientation
BLTA OrientationBLTA Orientation
BLTA Orientation
 
Session 3
Session 3Session 3
Session 3
 

Data collection

  • 1. Sponsored by FDLRS Action Resource Center
  • 2. Assessment  Measurement  Legal Accountability  Collaboration  Documentation  Problem Solving  Monitoring  Provide Feedback Diana Ferreira, Amy Rowe and Ann Cacciatore, OCPS
  • 3. Factual and unbiased information  Information is used for both academic and behavioral programming  2 critical components to data collection  Information gathering  Decision making
  • 4. • Problem Define Solving/RtI What is the problem? Is it working? • CPI COPING Model Academic • Data-based Evaluate & Analyze Decision Behavioral Making Model Why is it occurring? • Continuous What intervention am I going to do? Implement Improvement Model
  • 5. SUBJECTIVE (UN- OBJECTIVE (MEASURABLE) MEASURABLE)  Logan throws a tantrum  Logan cries and kicks when he does not get his objects/people when he way. is denied access to the computer.  Angelina will identify  When given a verbal numbers. prompt “touch the number ___”, Angelina will expressively identify the requested number given an array of 3 choices.
  • 6. Is objective and non-judgmental  Helps to define the problem  Original data (before any intervention has taken place)  Is used to compare and evaluate the effectiveness of the intervention
  • 7. Event Recording / Frequency Record how many times a behavior occurs Green Duration Used to document the amount of time a student Blue spends in engaging in a behavior A-B-C Antecedent – Behavior – Consequence Purple Documents what occurs before/after a behavior Percent Correct Number of correct responses divided by the total Pink number of opportunities to respond Latency Documents how long it takes for a behavior begin Orange after a demand or event occurs Diana Ferreira, Amy Rowe and
  • 8. Be consistent in the type of data collected  Ensure that all who are taking data have been trained and understand the data collection tool being used.  Does intervention/data collection plan pass the “Stranger Test”?
  • 9.
  • 11.
  • 12. What system(s) do you have in place for managing the sometimes overwhelming amount of student data that is collected?
  • 13. Must occur to be able to analyze the data collected  Quick and easy visual summaries that allow for easy determination of  patterns of behavior  evaluate results on new teaching strategies  determine if interventions are/are not having the desired effects
  • 14.
  • 15.
  • 16.
  • 17.
  • 18. Review data points every 3 sessions  Ask yourself is the data…  Improving?  Staying the same (flattening)?  Worsening?  Make a decision!
  • 19. Possible Actions:  Continue services and supports with current annual goal.  Continue services and supports and increase annual goal.  Gradually fade services or supports to determine if the student can perform independently. 19
  • 20. Possible Actions: Determine if the services and supports were implemented as intended.  If not, improve implementation of services and supports.  If yes, increase intensity of current services and supports and assess impact. If rate doesn’t improve, return to problem 20 solving.
  • 21. Possible Actions: Determine if the services and supports were implemented as intended.  If not, improve implementation of services and supports.  If yes, return to problem solving. 21

Hinweis der Redaktion

  1. Sketch your classroom
  2. Assessment-objective assessment of behavior changeMeasurement-student making progressLegal accountability-Communication-Across settings and peopleDocumentation-Prevents relying on memoryProblem solving-Difficulties in progressMonitor-Determine effectivenessProvide feedback-To students parents and staffAt a meeting, rather than saying Michael never does any work. It would be much better to pull data which shows that Michael is only on task 50% of each class period.The IEP will drive your data collection and makes you responsible for providing information about behavior and social skills in a logical, precise, tangible method.
  3. Props: index card file folder, post-it note folder, ring w/ cards, binders, etc.
  4. In reviewing the IEP, the student’s rate of progress and the likelihood of achieving the annual goals should be the first indicator of how well the IEP is working for the student.The student’s progress towards the annual goal is measured through ongoing data collection. To determine if the response has been positive, the teacher or the IEP team will look at the data to see if the gap between current and expected student performance is closing. The expected performance is the target set in the annual goal. Take a look at this graph of student progress. The green line shows the expected rate of progress for the student to reach the goal. The dotted line shows the student’s actual progress. Does the gap between the two appear to be closing? Yes!If the response has been positive, the following actions are possible:Continue services and supports with current annual goal.Continue services and supports and increase annual goal.Gradually fade services or supports to determine if the student can perform independently.This may look familiar to you. This decision rule is from the PS-RtI framework. The progress-monitoring data charts and descriptions of possible actions are adapted from the book Guiding Tools for Instructional Problem Solving (GTIPS) (2011). Hold up the GTIPS Book.Note: If participants inquire about where to find graphing programs, mention that progress-monitoring software is sometimes available with their reading and mathematics curricula. If not, they can create progress-monitoring graphs using database software such as Excel. Graphing programs for progress monitoring are also available for download online.
  5. A questionable response is when the rate of progress is not sufficient to close the gap, as shown in this graph.If the response is questionable, the following actions are possible:Determine if the services and supports were implemented as intended. This is where monitoring with integrity comes into play. If not, improve the implementation of services and supports.If yes, increase intensity of current services and supports and assess impact. If the rate of progress doesn’t improve, return to problemsolving.
  6. A poorresponse is when the gap continues to widen with no change or improvement in the rate of progress.If the response is poor, the following actions are possible:Determine if the services and supports were implemented as intended, including instruction, accommodations, etc.If not, improve implementation of services and supports.If yes, return to problemsolving. Review student data to make sure the correct problem is identified and/or change the instructional strategy or supports as needed (e.g., change an accommodation that does not appear to be enabling the student to perform as anticipated).