1. 1 Milwaukee Mathematics Partnership The Relationship between MMP Involvement and Student Achievement MPS Research Brief Carl Hanssen Hanssen Consulting, LLC Cindy Walker UWM May 27, 2010

2. 2 Agenda 1. Funding 2. MMP Involvement Metric 3. Results 4. Next Steps

3. 3 Funding  Original MMP funding from NSF started in 2003 currently in 7 th year  MMP Phase II funding from NSF awarded 2009 for 3 years Heavy focus on research and evaluation  State of Wisconsin Provides funding for released MTL positions

4. 4 MMP Involvement Key Question: Is there a relationship between involvement in MMP activities and student achievement? Critical Challenge: Quantifying ‘involvement’

5. 5 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)

6. 6 MTL Meeting Attendance  9 meetings each year  In 08-09 there were also Grade 8-9 meetings  This factor is the % of meetings where a school was represented by at least 1 person.  No extra credit for having more than one person at a meeting

7. 7 Course Attendance  MPS teachers had the opportunity to attend content courses sponsored by UWM  Factor combines three elements: 1. Number of unique teachers in a school taking at least 1 course 2. Average number of courses enrolled 3. Average number of credit earned  Rewards schools that had many teachers taking many courses

8. 8 Action Planning  Each school had the opportunity to apply for mini-grants to implement school-specific strategies for math improvement  This factor was either yes, or no— did the school receive funds?  Effective utilization of funds could not be determined based on available data

9. 9 Textbook Adoption  This factor reflects participation in the 05- 06 textbook adoption process  The factor reflects number of sessions with at least 1 staff member in attendance + average number of staff attending each session  Rewards consistent and broad representation in the process

10. 10 Algebra & Geometry Labs  This factor reflects participation in the labs for HS teachers only  The factor reflects number of unique teachers attending at least 1 lab + the average number of labs each teacher attended.  Rewards broad and consistent participation

11. 11 Factor Weighting  Each factor was then weighted based on importance and to balance absolute score differentials 1. MTL Meetings4X 2. Course Attendance1X 3. Action Plans2X 4. Textbook Adoption.5x 5. Lab Attendance.5x

12. 12 Final Involvement Calculations  Within each year, the weighted factors were summed to quantify MMP Involvement for that school for that year.  Cumulative involvement was quantified by summing involvement across all MMP years.

13. 13 Cumulative Involvement— Schools Serving Grade 10 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

14. 14 Schools with Grade 10 Students

15. 15 Cumulative Involvement— Schools Serving Grades 6-8 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

16. 16 Schools With Grade 6-8 Students

17. 17 Cumulative Involvement— Schools Serving Grades 3-5 These data are then converted to z-scores And schools grouped as No-Low-Medium-High

18. 18 Schools With Grade 3-5 Students

19. 19 Wrap Up  This work is an attempt to quantify involvement in the MMP and relate that to student achievement.  Initial results suggest that involvement is a predictor of student achievement—most notably between the no-involvement and other groups.  Future analyses will examine achievement growth as well as further refine the involvement metric.

20. 20 Contact Information Carl Hanssen mmp@hanssenconsulting.com 616-808-2867