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Harvesting Data for Problem Solving REBECCA PIERMATTEI Wayne Hickman Christina Jordan

Harvesting Data for Problem Solving REBECCA PIERMATTEI Wayne Hickman Christina Jordan. PBIS Maryland Coaches Meeting April 30, 2014 & May 5, 2014. WHAT CAN WE LEARN FROM DATA?. What we are doing well and what challenges we face Which students, teachers, systems need more support

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Harvesting Data for Problem Solving REBECCA PIERMATTEI Wayne Hickman Christina Jordan

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  1. Harvesting Data for Problem SolvingREBECCA PIERMATTEIWayne HickmanChristina Jordan PBIS Maryland Coaches Meeting April 30, 2014 & May 5, 2014

  2. WHAT CAN WE LEARN FROM DATA? • What we are doing well and what challenges we face • Which students, teachers, systems need more support • Whether our support is successful

  3. In a Nutshell • Know what data you need and how to access the data. • Make sure your data is reliable • Review and share data on a regular basis. • Keep it simple and reasonable. • Use your data to guide your decision making. • Use your data to evaluate individual progress as well as program and school-wide success.

  4. BEFORE YOU START… Resource Mapping

  5. Resource Mapping-Inventory of Current Practices • What are the practices in place at each tier of the triangle? • Are they evidence-based practices? • How are you measuring effectiveness of practices (data)? • Who are the service delivery teams/personnel (e.g., graduation coach, PALS teacher, Math Coach)

  6. Triangle Activity: Applying the Three-Tiered Logic to Your School Tier 3 Practices, Initiatives, Programs for a FEW Tier 2 Practices, Initiatives, Programs for SOME Tier 1 Practices, Initiatives, Programs for ALL

  7. BEFORE YOU START… • Resource Mapping • Early Warning Indicators

  8. Part A: SCHOOL-WIDE DATA • Identify what academic and behavioral data you need • ACADEMIC: Homework completion, GPA, Credit Accrual, Benchmark Assessments • BEHAVIORAL: ODRs (Big 5), attendance, suspension/expulsion, minor incidents, nursing and counseling logs • Identify the sources of that data • Identify the person responsible for getting and presenting the data • Identify how often and it what manner it will be shared with the team, faculty, and administration

  9. Part B: WHAT DO WE DO WITH THE DATA? • Celebrate success! • Identify problems with PRECISION using the 5 W’s: • What, Where, When, Who, Why • Determine whether your data indicates a need for school-wide practice or small group/individual response? • Develop Solution Options • Create Problem Solving Action Plan • Evaluate Solution

  10. HELPFUL TOOLS • Data Decision Rules • Problem Solving Action Plan

  11. EXAMPLE • PRECISION PROBLEM STATEMENT: Many students from all grade levels are engaging in disruption, inappropriate language, and harassment in the cafeteria and hallway during lunch, and the behavior is maintained by peer attention. Identify 5 W’s Identify which system you will target

  12. TIER 2/3: Sorting Students into Interventions ACTIVITY

  13. BEFORE YOU START… • Resource Mapping • Early Warning Indicators • Decision Rules for Access to Interventions

  14. Decision Rules for Access to Advanced Tiers • Specific to each intervention • Identify objective variables/criteria as well as the minimum/maximum for each • EX: GPA between 1.0 and 1.5 • You may need to scale up or down depending on your capacity

  15. Part C: Sorting Students into Interventions • 1. How will students be identified for this intervention? What are the data decision rules for access – criteria used, min and max for each variable? • 2. What data do we need? • 3. Where will we get the data? • 4. Who will be responsible for collecting the data?

  16. HELPFUL TOOLS • EARLY WARNING INDICATORS • RESOURCE MAPPING • DECISION RULES FOR ACCESS TO ADVANCED TIERS

  17. Part D: Progress Monitoring and Program Evaluation • How will student progress be measured/monitored? Who is responsible for measuring/monitoring progress? • What indicators/benchmarks will show that a student is responding to the intervention? Not responding? • What indicators/benchmarks will show that a student is ready to exit the program? 4. How will overall program success be measured/monitored?

  18. HELPFUL TOOL • Intervention Tracking Tool *Illinois PBIS Network

  19. OH NO! What do you do if your data shows your program is not working?

  20. FIDELITY MEASURES • Determine whether you are implementing with fidelity (Are you doing it the way you are supposed to be doing it?) • Consider BOQ, SET, PBIS-TIC • Consider intervention specific fidelity measures

  21. IMPORTANT CONSIDERATION DATA MUST BE RELIABLE • EXAMPLE: Behavior Referrals • Define your behaviors • Agreement re: major/minor • Standardized procedures for gathering referrals • All staff trained in how to complete and submit referrals

  22. In a Nutshell • Know what data you need and how to access the data. • Make sure the data is reliable • Review and share data on a regular basis. • Keep it simple and reasonable. • Use your data to guide your decision making. • Use your data to evaluate individual progress as well as program and school-wide success.

  23. Acknowledgements • MDS3 is funded by a grant from the USDOE. • Federal Grant CFDA# Q184Y100015 • Sheppard Pratt Health System: • Rebecca Piermattei, M.S. Rpiermattei@mds3online.org • Wayne Hickman, Ed.D. Whickman@mds3online.org • Christina Jordan, M.Ed. Cjordan@mds3online.org • Maryland State Department of Education • Johns Hopkins University

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