1. Using Data to Manage Interventions Managing student supports within City Year and Diplomas Now

2. Fill out the chart provided with as many examples of relevant data that you or teams you work with might use in schools. Do Now

3. Objectives At the end of this session participants will Understand data context and terminology for Diplomas Now and City Year sites Understand uses of data in school contexts

4. Kellie Hinkle: Diplomas Now Manager of School Turnaround, CYHQ Dan Anderson: Talent Development Facilitator at the Jeremiah E. Burke High School Who We Are

5. Agenda (90 minutes) Do Now (5 minutes) Agenda (5 minutes) Data Review (20 minutes) Managing the Data (10 minutes) Data Sorting Activity (25 minutes) Q & A (15 minutes) Wrap Up and Evaluation (10)

6. Data Review

7. What examples of data did you come up with that would shed light on student patterns in Attendance, Behavior, and Coursework? Data Review

8. Student average daily attendance – Days missed, attended and excused – Sorted by student, homeroom, grade, etc. Student tardy rates – How often are students late? – How late are they? Logs of phone calls to students and families regarding attendance Examples: Attendance

9. Suspensions Detentions Referrals of students for behavior reasons to administrators, student support, etc Behavior management/PBIS information Results of student risk and character skills assessments such as Success Highways Examples: Behavior

10. Results of diagnostic assessments – DIBELS, GRADE, GMADE, ANet, Gates-MacGinitie – Assessments of skills in various areas, such as fluency, vocabulary, reading comprehension, etc Course grades – Viewed by student, course, section, etc Results of state test scores and predictive diagnostics Results of teacher-designed formative and summative assessments Examples: Coursework

11. Indication of dropout risk Research based DN 101: What Is an EWI? Indicator AreaOff-TrackSlidingOn-Track Attendance<85% ADA85-90% ADA>90% ADA Behavior>0 suspensions0 suspensions Coursework (ELA and Math) Course grade of FCourse grade of DCourse grade >D EWIs – early warning indicators ABCs – (poor) Attendance, (disruptive) Behavior, Course performance (failure in English and/or math)

12. DN Goals Off TrackOn Track Attendance: <90% average daily attendance≥90% average daily attendance Behavior: 1 or more suspensionsno suspensions ELA/Literacy: a “D” or an “F” ELA gradea “C” or higher ELA grade Math: a “D” or an “F” math gradea “C” or higher math grade DN goals – At least 67% of students in focus grades have no EWIs at the end of the school year – For each ABC: ≥50% of students with an EWI at any point move on- track by the end of the year

13. There are a number of tools, processes and systems in which data is used in Diplomas Now: DN focus list DN quarterly reports School-based data systems EWI meetings Data Use for Diplomas Now

14. DN Focus List A collaborative process: the entire DN school team (and school faculty, if available) should work together to identify students For all students in need: any student with an EWI should be on the focus list in the indicator area(s) in which they need help

15. DN Quarterly Reports

16. Goal: To coordinate and create interventions for students who are exhibiting early warning indicators and to closely monitor their progress towards success. These meetings: Are an opportunity for all the adults in a school that work with a particular set of students to come together to:  analyze data  craft interventions  project manage existing interventions Occur at least every other week for each adult team in the school Early Warning Indicator Meetings

17. Managing the Data

18. Components – Compiling and utilizing data – Using the focus list – Holding EWI meetings Managing the Data

19. 1.Determine what data you need to track 2.Determine how you need to use your data 3.Determine whether you will use a school- or district-provided data management system, or manage your own Compiling and Utilizing Data

20. Example of Data Dashboard

21. Using the Focus List

22. Holding EWI Meetings

23. Data Sorting Activity

24. Take 25 minutes to go through the table provided to plan managing data this year Choose the table specifically designed for: – Staff responsible for a specific school site – Operations staff We will circulate to answer questions After the activity we will have further time for questions Data Sorting Activity

25. Q & A

26. What questions do you have about expectations for data use or how to manage it? What do you feel like you still need to know or could use further coaching/development in with regards to data? Q & A

27. WSWC Attendance – days enrolled & days absent (per month) Behavior - # of suspensions per month Math & Literacy – Assessment scores (minimum 2 per student) Math & Literacy – Prior Year Grade, Each MP Grade, End of Year Grade DN Only Math & Literacy – Assessment scores (minimum 2 per student) Data Requirements for City Year

28. Thanks! Dan Anderson: dan.anderson@jhu.edudan.anderson@jhu.edu Kellie Hinkle: khinkle@cityyear.orgkhinkle@cityyear.org

29. On a notecard, please provide us with feedback: – Pluses (+): What helped your learning during this session? – Deltas ( ∆ ): What impeded your learning during this session? Evaluation

30. PITW # 83: Give Immediate Feedback Follow the link in your email to complete the Learning Evaluation Survey. or If you did not receive an email, please go to the Summer Academy 2013 page on cyconnect. Select the “Learning Evaluations” link on the left side of the page and choose the appropriate survey. Learning Evaluation Surveys