1.  EWS Getting started  Risk Metrics  Excel for dispro  Tier 1 and Tier 2 plans  Background form

2. Culturally Responsive Early Warning System Use in a Multi- Level System of Support Christine Budnik, Assistant Principal Kelly Rohr, RtI Coordinator Manee Vongphakdy, School Counselor and EWS Coordinator Jill Koenitzer, WI RtI Center Technical Assistance Coordinator

3.  Rationale for Implementation of RtI – A and RtI – B  Specific Steps to Implementation  Culturally Responsive Early Warning System (CR-EWS)  Evaluation data from Wausau East

4.  Wausau, WI; population: 39,106  Number of Students at East: 1050  Demographics:  2.5% American Indian  4% Hispanic  5%African American  18% Asian  71% White  International Baccalaureate School

5.  High performing students and system which met student needs  Evolving student population  System not meeting changing needs  Teachers struggling to meet needs of all students  Budget restraints  Frustrations began to build  Needed to do something…but what?  Began exploring options

6.  East HS Common Intellectual Mission: 21 st Century College and Career Ready  Gather  Analyze  Synthesize  Understand  Create Focus of year-long, staff training and collaboration

12.  Academic Enrichment Program  Identified students at-risk of not graduating and/or not being successful at East  Involved 9 th - 12 th grade  Small class size (8/teacher)  Worked with students on homework  Success in making connections with some students  Gut feeling’ identification- Struggle to find ‘right’ students

13.  Supportive building administration  Research and Design Committee  Teachers, administrators, counselors- ‘problem solving’ committee  Caring staff  Realization that things needed to change

14.  Stronger impact on ALL students  Efficient use of existing data  Effective System to identify at-risk students earlier  Time, money, resources….. Began to research what was out there

15.  Other schools  Staff Development  Books  Conferences  Online Resources Needed a plan to pull everything together…

16.  Team from East attended workshop: WI RTI Framework: A Systems Approach to RTI  Regular Education Teachers (English, Science, Math, Social Studies), SPED, School Counselor & Psychologist, Assistant Principal  Met helpful WI RtI staff (Jill Koenitzer)  Introduced to the Early Warning System  Began to identify biggest struggles  Began to develop a plan

17.  LOTS of questions!  Where do we begin?  Could be identify what was/was not working?  Could we get people to change?  Who was going to be involved?  Where would we find the time?  How could we use the information from the conference effectively? More questions than answers…

18.  Created East RTI Committee  Involved in Early Warning System (EWS)  Academic Enrichment program changes  Resource Center changes  Stronger communication between all parties  Hard and honest look at data-

19.  Participants: Kelly Rohr(English), Hope Cameron(Social Studies), Julia McMahon(Math), Darlene Beattie(Science), Lou Livingston(SPED), Manee Vongpakte(Counselor), Joe Svitak(AP), Chris Budnik(AP), Rich Ament(School Psych), Sara Boetcher(District RTI Coordinator)  Meeting Time: 2X/Month (Collab Time)  Administrative Support: VITAL  Staff Buy-In: Communication was crucial  Early Warning System: Putting it in place

20. http://www.betterhighschools.org/EWS_imp.asp

21.  Worked with Wisconsin RtI Center  Pulled data together-  Focus on one grade- 9 th  Educate staff on EWS  How do we use the data?  1 st year discoveries

22.  Resource Centers-  Use of commons, LMC  RC assignments  Academic Enrichment-  Use of Data-  Coordinator-  Staff Buy-In VITAL

23.  Full-time Math RC teacher  Full-time English RC teacher  Assigned students to RC  EWS students  D/F students (Progress Report/Quarter grade)  Teacher request- Intervention Forms  Stronger teacher involvement  RC Binder  Communication

24.  Developed Curriculum Guide  Student, teacher and parent expectations  Identified specific skills necessary for success  Academic Seminar (2015/2016)?  Focus on 9 th and 10 th graders  Use data to identify students  Goal setting  Self advocacy  Communication  Scheduling

25.  EWS  At-risk identification  Quarterly results  Semester results  Results drive meetings  Lexile Testing  School SLO  All freshmen tested (Fall, Winter, Spring)  Teacher use of scores

26.  Planned for.8 position (.2 AE)  Scheduled in English RC  AE connection  Monitor EWS students  Coordinate RCs  Staff Development  Schedule EWS students  And…and…and…

27.  VITAL!  Tier 1 Instruction and Support (Collab time)  Disciplinary Literacy  Formative Assessments  Academic Vocabulary  Lexile Use  Differentiation  RC Expectations  Student Motivation  Patience  Results

28.  Tier 1 Intervention Form  Tier 2 Academic Intervention Plan  RTI Background Form  Tier 2 Teacher Response Form  Articles  Training Opportunities

32.  Staff Buy-in  Administrative Support  System Change- TIME  Data Retreat  Literacy Coach  Additional Training

33.  Hand-scheduling students with EWS flags  Freshman homerooms  LINK crew  Connections Survey  Check In/Check Out  Academic Seminar pilot

34. Identifying disproportionality

35. Discipline ODRs Suspension / Expulsion Attendance Early Absences Chronic Absence Course Performance Grades GPA

36. Identify disproportionate data at the school level Decision rules: How do we determine when action is needed? Use multiple metrics Adapted from: “Hope is Necessary but not Sufficient: Using Data to Address Disproportionality,” Therese Sandomierski & Christopher Vatland, Florida’s Positive Behavior Support Project, Thursday, March 12 th 2015, APBS International Conference

37. With small groups, a few students can have a big impact May change how you intervene Be familiar with school-level demographics

38. Risk (“Risk Index”) % of students in a racial/ethnic group who have at least one referral Risk Ratio Risk of one group vs. risk of another group Best single measure to summarize a group’s risk Not as effective with N < 15 Composition % of students who received referrals who belong to a specific racial/ethnic group Flag Composition/Comparison % of referrals generated by a specific racial/ethnic group Impacted by students who receive multiple referrals

39. Total Flags per Child  Average Flags per child in a specific racial/ethnic group  Impacted by students who have multiple flags E-Formula Designed for “small-n” scenarios Standard error for Composition (the percent of students who have a flag who belong to a specific racial/ethnic group)  If a group’s Composition is greater than or the E-Formula value, disproportionality is indicated

43.  NOT cohort data  9 th grade: Quarter 1, 2, 3  10 th grade: Quarter 1, 2, 3

52. Kelly Rohr Chris Budnik Manee Vongphakdy Jill Koenitzer krohr@wausauschools.org cbudnik@wausauschools.org mvongpha@wausauschools.org koenitzerj@wisconsinrticenter.org