DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans...
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![Page 1: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/1.jpg)
DATA-BASED DECISION MAKINGUsing Outcome and Fidelity Data with Individual Student Support Plans
Session E12
Kelsey R. Morris, EdD—University of OregonDiane LaMaster—Illinois State Technical Assistance Collaborative
![Page 2: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/2.jpg)
•Session Overview• Progress monitoring student-specific, behavior support
plans
• Selecting and prioritizing target behavior(s) to monitor
• Implementing a measurement system
• Evaluating behavioral progress monitoring data to inform intervention decisions
•Goal• Plan and carry out data collection to monitor target
behavior
• Use graphed progress monitoring data to determine when intervention changes are needed
![Page 3: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/3.jpg)
Maximizing Your Session Participation
• Where are you in your implementation of the concepts presented?• Exploration & Adoption
• Installation
• Initial Implementation
• Full Implementation
• What do you hope to learn?
• What new learning do you take away from the session?
• What will you do with your new learning?
![Page 4: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/4.jpg)
Data-based Decision Making• Effective teams use data to document progress and outcomes, guide
decisions, and inform stakeholders (Boudett, City, & Murnane, 2006; Burke, 2010; Deno, 2005; Hill 2010; Newton, Algozzine, Algozzine, Horner, & Todd, 2011; Newton, Horner, Algozzine, Todd, & Algozzine, 2009; Pidgeon & Gregory, 2004; Renfro & Grieshaber, 2009)
• A critical predictor of sustained implementation of SWPBIS (Coffey & Horner, 2012; McIntosh et al., 2013)
• Fidelity and student outcome data are essential (Fixsen, Blase, Metz, & Van Dyke, 2013)
• Continues to be a struggle for schools (Dunn, Airola, Lo, & Garrison, 2013; Schildkamp, Ehren, & Lai, 2012; Telzrow, McNamara, & Hollinger, 2000)
• Advances in computer technology could provide efficient means for data management (Wayman, 2005)
![Page 5: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/5.jpg)
Intensity of Supports• Essential Question
• Is the student successful with this level of support?
• Intensity is a two-way street.• Improved student outcomes are
the result of continually monitoring and modifying (as needed) instruction, interventions, and supports.
![Page 6: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/6.jpg)
Essential Tier III Systems ElementsCoordinating Team
Tier III systems planning team meets regularly
Team has an identified leader
Membership represents behavioral expertise, administrative authority, intensive support expertise, knowledge about students, and knowledge about school operations
Student Support Team
A uniquely constructed team exists for each individual student support plan
Student support team is comprised of relevant stakeholders
Student support team exists to design, implement, monitor, and adapt the student-specific support plan
Data-based Decision Making
Outcome and fidelity data are reviewed by a student’s support team at least monthly
Data are used to modify the support plan to improve behavior outcomes and improve fidelity of implementation
![Page 7: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/7.jpg)
Student Support PlanHypothesis Statement
• Operational description of problem behavior
• Identification of context where problem behavior is most likely
• Maintaining reinforcers (e.g., behavioral function) in the identified context
Comprehensive Support
• Teaching strategies
• Strategies for removing rewards for problem behavior
• Specific rewards for desired behavior
• Safety elements, as needed
Systematic Evaluation
• Process for assessing fidelity
• Process for assessing outcomes
• Action plan for implementation
![Page 8: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/8.jpg)
Intensity of Assessment
Universal—primary prevention• Monthly
Secondary—small group, targeted• Weekly or twice monthly
Tertiary—individualized, intensive• Daily or multiple times per week
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Progress Monitoring• Progress monitoring is the process of systematically
planning, collecting, and evaluating data to inform programming decisions.
• Helps determine intervention effectiveness
• Helps in the development of effective support plans
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Planning Progress Monitoring• Selecting target behaviors is part of planning for behavioral
progress monitoring.
• Plan for data collection• Select target behavior(s) to monitor
• Choose method for monitoring the behavior(s)
• Create a plan for collecting data (e.g., schedule, person(s) responsible)
• Collect data
• Evaluate data to make decisions
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Selecting Target Behaviors• Identify the target behavior(s) of concern
• What does it look like? When does it occur? What is the perceived motivation?
• Define the target behavior(s)• A clear definition allows us to collect more reliable data
• Can you see it? Can you measure it? Do you know what it is and is not?
• Prioritize the target behavior(s)• More feasible data collection
• More efficient data analysis
• More effective decision making because the most important behavior is the focus
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Develop a Measurement Approach
Considerations:
• How often will data be collected?• Related to intensity of behavior and timelines for making
intervention decisions
• Where will data be collected? What context(s)?
• When will data be collected?
• Who will collect the data?• Consider when, where, and how the data will be collected
• When and how will the data be entered to allow for analysis?
![Page 13: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/13.jpg)
Adult Behaviors Cause Student Change
Outcomes Fidelity
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Monitoring and Evaluating Progress• Involves examining the progress monitoring data to
determine if the student is responding to the intervention and supports.
• Involves managing and organizing data to support summary and analysis.
Consider:• Do you have a data system that supports graphing?• Who will be responsible for entering the data?• Who will be responsible for generating graphs/reports?• Who will review/analyze the data?
![Page 15: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/15.jpg)
SIMEOSystematic Information Management for Educational Outcomes
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SIMEO II• Online data collection and graphing database system
used to assist PBIS tier III student/family teams with data-based decision making.
• Access to this data through a virtual connection • 24 hours a day, 7 days a week
• Password protected
• Graphing capability
![Page 17: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/17.jpg)
SIMEO Tools and Data• Student support teams use SIMEO to/for:
• Engage students, families, & teachers
• Team development & team ownership
• Ensure student/family/teacher voice• Identifying true needs and prioritizing items
• Effective interventions• Serious use of strengths
• Natural supports
• Focus on needs vs. services
• Progress monitoring and sustainability
• System support buy in
![Page 18: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/18.jpg)
SIMEO Tools at Tier III• Student Disposition Tool (SD-T)
• Complex FBA/BIP and Wraparound
• Education Information Tool (EL-T)• Complex FBA/BIP and Wraparound
• Home, School, Community Tool (HSC-T)• Wraparound and RENEW
• RENEW High School Youth Status Tool• RENEW H.S.
![Page 19: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/19.jpg)
Home, School, Community Tool (HSC-T)
• 33 items to assist teams with capturing strengths and needs of the student/family across home, school and community
• Questions address life domain areas:• Safety/Medical basic needs
• Social relationships
• Emotional functioning
• Behavioral functioning
• Cultural/Spiritual
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HSC-T
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Milton’s HSC-THOME SCHOOL COMMUNITY
Student’s family needs to know he is safe. Student needs to learn skills to be independent at home and in the community.
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Milton’s Student Disposition Tool (SD-T)At Risk of Failure in Home, School, Community Placements
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Jude’s HSC-T
Utility: engage the family and identify needs at baseline
HOME SCHOOL COMMUNITY
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Jude’s HSC-T Progress Monitoring
HOME SCHOOL COMMUNITY
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Longitudinal Data
HOME SCHOOL COMMUNITY
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Jude’s Student Disposition Tool (SD-T)
B T2 T3 T4 T5 T6 T7
ODR
16 13 20 1 6 1 5
ISS
2 2 4 0 0 0 0
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Jude’s Education Information Tool
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ISIS-SWISIndividual Student Information System
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Individual Student Information System
• ISIS-SWIS is a decision system for students receiving more intensive, individualized supports for academic, social, or mental health services.
• Allows for:• Uploading and storing documentation
• Defining data collection measures
• Summarizing data for decision making
![Page 30: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/30.jpg)
Advantages of ISIS-SWISEfficiency
Structured creation and maintenance of student files
One home for progress monitoring, goal setting, and decision making
Instantaneous access to data
Equity
Equal access to quality support plan management
Enabling of clear roles, responsibilities, and predictability
Quality
Supports compliance with federal procedures for Tier III support
Comprehensive student file for quality decision making
Documentation of progress and intervention history
Flexibility
Files and measures tailored to a student’s needs
![Page 31: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/31.jpg)
ISIS-SWIS Main
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ISIS-SWIS School-wide Reports
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Student File: Brian Bender
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Data Entry Aligned with Measures
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Brian: Assignment Completion
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Brian: Assignment Completion & Asking For Help
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Carly: Rate of Disruption & Staff Fidelity
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ISIS-SWIS Study• The Effects of Self-delivered Performance Feedback and
Impact Assessment via the Individualized Student Information System (ISIS-SWIS) on Behavior Support Plan Treatment Fidelity and Student Outcomes (Pinkelman, 2014)
• Study Conditions
• Researcher as ISIS-SWIS Faciliator• Provide ISIS-SWIS training
• Provide follow-up coaching and support
• Provide ongoing technical assistance
• Trained teachers as ISIS-SWIS Coordinators
• Trained educational assistants as ISIS-SWIS Users
• Held weekly meetings with teachers and educational assistants
![Page 39: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/39.jpg)
Teachers as ISIS-SWIS Coordinators• Manages student educational program
• Manages student file in ISIS-SWIS
• Outcome• Teacher competent in using ISIS-SWIS
• Student file established and ready for use
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EA as ISIS-SWIS User• Team member who needs access to student file
• Enter data into ISIS-SWIS• Self-monitor fidelity data
• Fidelity checklist
• Rating scale (0-5)
• Student outcome data• Percent of points earned
• Frequency of problem behavior
• Number of teacher directed tasks
![Page 41: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/41.jpg)
Weekly Meetings• EA, teacher, and researcher
• To ensure EA was using ISIS-SWIS regularly• Praise for using specific features of ISIS-SWIS regularly
• Identify features not being used
• Model, practice, and give feedback for features not being used
• Agreement for use
• Review graphs for data-based decision making• Is the plan being implemented with fidelity?
• Is the plan effective at improving student behavior?
• Do any changes need to be made?
![Page 42: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/42.jpg)
Results: Fidelity
Baseline ISIS-SWIS
Observed Fidelity
Per
cen
tage
BS
P C
omp
onen
ts
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Results: Fidelity & Academic
Engagement
Baseline ISIS-SWIS
Academic Engagement
Per
cent
age
BSP
Com
pone
nts
Percent 10 s Intervals A
E
Observed Fidelity
![Page 44: DATA-BASED DECISION MAKING Using Outcome and Fidelity Data with Individual Student Support Plans Session E12 Kelsey R. Morris, EdD—University of Oregon.](https://reader035.fdocuments.in/reader035/viewer/2022070323/56649d9d5503460f94a86b21/html5/thumbnails/44.jpg)
Results: Fidelity & ProblemBehavior
Baseline ISIS-SWISP
erce
nta
ge B
SP
Com
pon
ents P
ercentage 10s In
tervals
PB
Observed Fidelity
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Takeaways• Tier III progress monitoring should be individualized just
as the Tier III supports are individualized.
• Student outcome and implementation fidelity data are critical
• Data-based decision making continues to be difficult for schools (Dunn et al., 2013; Newton et al., 2012; Schildkamp et al., 2012; Telzrow et
al., 2000).
• A lack of efficient tools and systems to assist in data collection, organization, and summarization impedes the process.
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DATA-BASED DECISION MAKINGUsing Outcome and Fidelity Data with Individual Student Support Plans
Session E12
Kelsey R. Morris, EdD—University of OregonDiane LaMaster—Illinois State Technical Assistance Center