1. Welcome To The November MTL Meeting Please move as close to the center of the auditorium when selecting your seats.

2. 2 Milwaukee Mathematics Partnership Program Evaluation Year 7 Results Carl Hanssen Hanssen Consulting, LLC November 2010 MTL Meeting

3. 3 Where are we?  MMP efforts have been ongoing since 2003  This is the 6 th year we have been conducting the evaluation  NSF and MPS Evaluation Efforts have become integrated

4. 4 MMP Support  Original & Phase II funding from NSF Started in 2003-04 Currently in 8 th year Focus on research and evaluation  MPS & State of Wisconsin Provides funding for released MTL positions Support for MTS Positions Funding for Evaluation

5. 5 Evaluation Goals  Help the MMP better serve its constituents and improve its effectiveness  Serve the broader mathematics education community through documentation and dissemination of MMP success factors

6. 6 Key Evaluation Question What are the critical factors or conditions promoted by the MMP that are related to student achievement?

7. 7 Agenda 1. Released and non-Released MTLs 2. MMP Involvement 3. Mathematical Knowledge for Teaching 4. Social Network Analysis 5. Breakout Discussion 6. Upcoming Evaluation Activities

8. 8 1. Released v. non-Released MTLs Key question: How does achievement differ in schools with released and non- released MTLs? Examine attainment and value added

9. Pre-released MTLs 9

10. First year released MTLs 10

11. Second year released MTLs 11

12. Findings  There was an initial bias toward providing underperforming schools with a released MTL  Over time, the position appears to have been effective for helping close the gap between low and high performing schools  In the most recent year, there is no statistical differences in quadrant membership between schools with and without released MTLs 12

13. Small Group Discussion  What other factors might help explain these findings?  How has having a released MTL (or not having a released MTL) made a difference in your school? 13

14. 14 2. MMP Involvement Key Question: Is there a relationship between involvement in MMP activities and student achievement? Critical Challenge: Quantifying ‘involvement’

15. 15 Involvement Factors  MTL Meeting Attendance  Course Enrollment  Action Planning  Textbook Adoption  HS Algebra and Geometry Labs Not all factors were present in each year (05-06 through 08-09)

16. 16 Cumulative Involvement— Schools Serving Grade 10 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

17. 17 Schools with Grade 10 Students

18. 18 Cumulative Involvement— Schools Serving Grades 6-8 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

19. 19 Schools With Grade 6-8 Students

20. 20 Cumulative Involvement— Schools Serving Grades 3-5 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

21. 21 Schools With Grade 3-5 Students

22. Findings  Initial results suggest that involvement is a predictor of student achievement—most notably between the no- involvement and other groups. 22

23. Small Group Discussion  In what ways does involvement in MMP activities translate to improved teaching and learning at the classroom level?  What other factors might help explain these results? 23

24. 3. Mathematical Knowledge for Teaching (MKT) Key Question: What is the relationship between teacher MKT and student achievement? Predict Fall WKCE scores for teachers’ prior year students 24

25. Teacher MKT Over Time 25

26. Distribution of 2008-09 Scores 26

27. WKCE Scores Fall 2009 27

28. HLM Results 28 After controlling for grade level, teacher MKT accounts for 4.6% of variability in WKCE scores

29. Small Group Discussion  What strategies can MTLs use to improve teacher MKT?  How can the MTSs support these efforts? 29

30. 4. Social Network Analysis Key Question: How have school-based networks changed over time? Social Network Analysis conducted in 112 schools in Spring 2009 30

31. 31 SNA Key  Maps identify MTL or MTS or Teachers Principal Literacy Coach Others in school Others outside school  Statistics Network density In-School density MTL In-Degree MTL Betweeness MTS In-Degree Principal In-Degree Benefit—a graphical AND statistical description of school-based networks.

32. Density Changes 32 2009 2010 Networks are becoming less dense

33. MTL In-Degree 33 Hi Lo

34. Hi MTL Betweeness 34

35. Hi MTS In-Degree 35

36. Hi Principal In-Degree 36 Principal

37. Findings  Strong networks manifest multiple characteristics—high density, MTL In-Degree & Betweeness, MTS In- Degree, and Principal In-Degree  The Release MTL Position may be eroding some characteristics of strong networks 37

38. Small Group Discussion  In Social Network terms, how would you describe your school?  How can MTLs and MTSs support the creation of strong distributed leadership in schools? 38

39. BREAKOUT DISCUSSION 39

40. Final Thoughts  There is no simple answer to the question of what drives student achievement  However…schools that demonstrate strong results tend to exhibit many of the positive conditions discussed today 40

41. 6. Next Steps 1. Teacher MKT Monthly sessions January – May Central Services Sign up starting in December More information forthcoming 2. MMP Online Survey—May 2011 3. SNA Survey—May2011 4. MTL Survey—April 2011 41