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

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

 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

 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

 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

 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

 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

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

 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

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

 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

 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…

 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-

 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

 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

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

 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

 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

 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

 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…

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

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

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

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

Identifying disproportionality

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

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

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

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

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

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

Kelly Rohr Chris Budnik Manee Vongphakdy Jill Koenitzer