Collaborative Inquiry

1. Collaborative Inquiry November 16, 2017 Margie Johnson, Ed.D. Brad Redmond

2. Today’s Outcomes • Provide an overview of MNPS’ Data-Informed Decision Making Ecosystem. • Model the MNPS collaborative inquiry process as an approach for developing a data-informed decision making culture.

3. Metropolitan Nashville Public Schools • 42nd largest school district in the US • 88,000 students; 6,000 teachers; 4,000 support staff • Students speak 100 + different languages • 160 buildings

4. Data Systems

5. Conducting a Needs Assessment • “Data” professional development documentation • Data warehouse utilization report • Data use research

6. Data-Informed Decision Making Ecosystem Johnson, 2016; Johnson, in press

7. Datahave nomeaning. Meaningis imposedthrough interpretation (Wellman & Lipton, 2004, pp. ix-xi).

8. How do we bridge the gap between data and results? Collaborative Inquiry Data Results Love, 2009

9. MNPSCollaborativeInquiry Collaborative Inquiry is a data-based team process that consciously uses the collaborative learning cycle(activating and engaging, exploring and discovering, and organizing and integrating) and the qualities of effective groups(fostering a culture of trust, maintaining a clear focus, taking collective responsibility and data-informed decision-making). MNPS Collaborative Inquiry Community of Practice

10. Modeling the Process

11. Purpose and Outcomes Ourpurposeistofosteracultureofcollaborationtosupportstudentsuccess. Our outcomes today are to model the collaborativeinquiryprocessfor analyzing MNPSattendancedata and making recommendations for improvement.

12. Activating and Engaging--Grounding TOPIC: ATTENDANCE • My name is … • My relationship to the topic is … • My expectations for today are …

13. Overview of Attendance Data Journey Brad Redmond

14. Common Contributing Factors to Poor Student Attendance Fear of a bully or of being teased Dislike/disinterest in school/lack of direction Problems at home Medical issues Peer pressure Drug use/abuse Transportation issues Health Problems Emotional or mental health problems Academic frustration and failure Perceived unfair treatment by school staff The idea that they have better things to do The mission of Support Services is to support the whole child by improving the conditions of learning while helping ALL students and their families overcome life’s challenges.

15. Understanding the Progression of Truancy Intervention Unpacking Attendance Terms

16. High Percentages of ADA Can Mask Chronic Absence 93% and even 95% ≠ A 98% ADA = little chronic absence 95% ADA = don’t know 93% ADA = significant chronic absence

17. The Scope of the Problem 2012-2017 MNPS Student Attendance Data

18. The Scope of the Problem 2016-2017 MNPS Chronic Absence by Grade Level

19. The Scope of the Problem Percent Students Scoring Proficient or Advanced Based on Attendance *Achievement Gap >20% in both subject areas across all tiers* Students can’t learn if they aren’t in school.

20. Understanding the Progression of Truancy Intervention 3 Tier Approach to Attendance Intervention Students with severe chronic absence and/or truancy Students with chronic absence or truancy over multiple years A small fraction of student body Recovery Programs Legal Intervention Some students Students at risk, or in the early stages, of chronic absence and/or truancy Intervention Programs Early Intervention: Reducing barriers to attendance Prevention: Establishing expectations and positive school climate School-wide strategy to promote & encourage regular daily attendance All students

21. Exploring and Discovering

22. Exploring and Discovering—Calibrating Activity

23. Exploring and Discovering—Data Dive Observations

24. CollaborativeLearningCycle Organizing and Integrating Activating and Engaging Managing Modeling Mediating Monitoring Exploring and Discovering --Lipton, L. & Wellman, B. (2012)

25. Organizing and Integrating--Recommendations Given the data observations, what might be some recommendations you have for improving attendance for MNPS students?

26. Wrap-Up

27. DebriefingQ & A

28. MNPSCollaborativeInquiry Collaborative Inquiry is a data-based team process that consciously uses the collaborative learning cycle(activating and engaging, exploring and discovering, and organizing and integrating) and the qualities of effective groups(fostering a culture of trust, maintaining a clear focus, taking collective responsibility and data-informed decision-making). MNPS Collaborative Inquiry Community of Practice

29. MNPS Collaborative Inquiry Toolkit www.mnpscollaboration.org

30. Reflection What might be some ideas you take from this session to implement in your organization and/or share with others?

31. Wrap Up

32. Contact Information and Questions Margie L. Johnson, Ed.D. margie.johnson@mnps.org Twitter: @MargieLJohnson3 www.mnpscollaboration.org Brad Redmond bradley.redmond@mnps.org

33. References Johnson, M. (in press). Empowering educators to make data-informed decisions: A district’s journey of effective data use. In E. Mense and M. Crain-Dorough (Eds.), Data leadership for K-12 schools in a time of accountability. Hershey, PA: IGI Global. Johnson, M. (2016). Experience from the field. In J. Rankin, How to make data work: A guide for educational leaders (pp. 171). New York City, NY: Routledge Love, N., Stiles, K.E., Mundy, S., & DiRanna, K. (2009). The data coach’s guide to improving learning for all students: Unleashing the power of collaborative inquiry. Thousand Oaks, CA: Corwin.