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Spring Data Review Workday District Leadership Teams

Spring Data Review Workday District Leadership Teams. May 29, 2014. The material for this training day was developed by Ingham ISD: Theron Blakeslee, John Endahl, Melanie Kahler, Matt Phillips, Jeanne Tomlinson, Kelly Trout, Laura Colligan and Mary Jo Wegenke

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Spring Data Review Workday District Leadership Teams

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  1. Spring Data Review WorkdayDistrictLeadership Teams May 29, 2014

  2. The material for this training day was developed by Ingham ISD: • Theron Blakeslee, John Endahl, Melanie Kahler, Matt Phillips, Jeanne Tomlinson, Kelly Trout, Laura Colligan and Mary Jo Wegenke Content based on the work of… • MiBLSi project • Steve Goodman, Anna Harms, Melissa Nantais, Jennifer Rollenhagen, Kim St. Martin, Tennille Whitmore • George Batsch, University of South Florida • Robert Balfanz, Everyone Graduates Center and • Johns Hopkins University • Roland Good and Rob Horner, University of Oregon • George Sugai, University of Connecticut • Joe Torgesen, Florida Center for Reading Research • Dawn Miller, Shawnee Mission School District, Kansas Acknowledgements

  3. Where to access materials for today: MTSS Implementers Website http://mtss-implementers.wiki.inghamisd.org  Building Data Review page 1. POMPOMS! The documents we are using today are on flash drives attached to ISD pompoms. OR Cute as they are, please don’t take them home! • Materials you will need today • Data Review Workbook(MTSS Wiki & hardcopy) • Problem Solving Guide (MTSS Wiki & hardcopy) • Worked Example Problem Solving Guide (MTSS Wiki & hardcopy) • Log-in Information: Illuminate, BAA, pbisapps.org, and SWIS • Process Data: PETR/SWEPT, PET-M, BSA, BoQ, SAS

  4. I can articulate… • the purpose and value in a District Data Review. • how process data can inform the district about current academic and behavior systems • how student outcomes data can inform the district about student performance. • how student outcome data and process data can be used together to inform district goals. • the purpose and steps in a problem solving process; gather data, identify and analyze problem(s), develop an action plan, and evaluate the plan. Learning Targets

  5. Time is an even higher commodity • Districts will have tensions between the needs of schools and the demands and resources available from the region and state • More data to analyze, analysis techniques will differ • Decisions and actions must take into account the entire district District evaluation of MTSS. . . not an exact replication of building-level problem solving

  6. The district data review process results in the identification of areas that the district schools need to prioritize • The priorities (findings from the data review) need to be communicated to the administrative team and to the building leadership teams and staff • Priorities and corresponding actions are documented in both the District Improvement Plan and the School Improvement Plan(s) • The district data review process looks for common implementation challenges across schools so that the district implementation team can work to eliminate barriers to successful implementation Describing the Connection

  7. New Page 4 in Data Tool Kit Evaluating Previous Plan

  8. I. GATHER Collect Data Data-based Problem Solving IV. DO Implement, Monitor & Evaluate II. STUDY Analyze & Problem Identification/ Analysis III. PLAN Develop Improvement Plan Problem Solving Guide

  9. Connection to School Improvement

  10. Scheduling of Action Items First Few Days of School

  11. What … Assumptions do we bring to this discussion? Important points seem to pop out? Patterns, categories, or trends are emerging? Seems to be surprising or unexpected? Additional data sources do we need to explore? Inferences, explanations, or conclusions might we draw? Solutions might we explore as a result of our conclusions? got data? Now What?, Solution Tree Press, 2012 Data Analysis…Something to think about

  12. got data? Now What?, Solution Tree Press, 2012 5 Reasons Why Problem Exists

  13. An issue recurs with frequency, year after year. • An issue is pervasive across multiple grade levels, student groups or school settings. • An issue consumes high levels of energy, time and resources. • Even after an improvement bump, performance plateaus and subsequent data flatline. • got data? Now What?, Solution Tree Press, 2012 Criteria for Pursuing Worthy Problems

  14. As seen at Building Data Days Process Data Snapshots: PBIS Self-Assessment Survey (SAS)

  15. Annual and/or Trend Data • Suspensions: % of students, events, and duration by grade level (elementary, middle, high school); EWS Target is • > 90% have 0 (zero) OSS • Triangle Data: Tiered report of Office Discipline Referrals • Ethnicity Reports District Outcome Data - Behavior

  16. Assign Roles • Review: • Materials • District Improvement Plan • Winter Action Plan • Begin Data Analysis Process Data (use the Process Data Overview Forms to record observations) Outcome data (use the District Literacy & Mathematics Overview Forms as a place to record observations) Current Performance, Trends, Special Education Review the School-wide overview forms from Building Data Review Prioritize areas of concerns across the district • Begin the problem solving process • Using ASSIST, enter the information into the District Improvement Plan Complete the Communication Plan Team Time

  17. Please Complete the Session Evaluation

  18. THANK YOU!

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