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Statistical Peers for Benchmarking 2007

Statistical Peers for Benchmarking 2007. River Dunavin Albuquerque Public Schools.

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Statistical Peers for Benchmarking 2007

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  1. Statistical Peers for Benchmarking 2007 River Dunavin Albuquerque Public Schools

  2. Using Statistical Peers to Benchmark School Performance and Increase Collaboration with Principals from Successful Schools Having Similar PopulationsCouncil of the Great City Schools Annual Fall Conference Nashville 2007 River Dunavin Albuquerque Public Schools

  3. Statistical Peers for Benchmarking • Grouping tool • Using tool with 2007 SBA results 3

  4. Jefferson MS Washington MS 12 Group Feeder System Albuquerque HS E. San Jose ES L. Wallace ES Monte Vista ES Longfellow ES R. Chavez ES Montezuma ES D. Gonzales ES E. Field ES Lowell ES Zia ES 4

  5. Statistical Peers for Benchmarking • Administrators & other educators ask, Which schools are most similar? 5

  6. Statistical Peers Purpose 1) Identify comparable schools using a data-driven strategy • Which schools have most similar student populations? 2) Encourage best practice collaboration 6

  7. Statistical Peers Development • Variables considered for grouping analyses: FRPM ELL Ethnicity Special Ed. Mobility Homeless Enrollment 7

  8. Statistical Peers Development • K-means cluster analysis assigns group membership • Panel of experts identifies best fit from several options 8

  9. Statistical Peers Development 26 APS Middle Schools Group A Group B Group C 9

  10. Albuquerque Feeder Group Statistical Peers Group 11 Albuquerque Jefferson Washington Dolores Gonzales East San Jose Eugene Field Lew Wallace Longfellow Lowell Monte Vista Montezuma Reginald Chavez Zia Statistical Peers Group 7 Statistical Peers Group 9 Statistical Peers Group 1 Statistical Peers Group 2 Statistical Peers Group 3 Statistical Peers Group 4 Statistical Peers Group 5 Statistical Peers for Benchmarking 10

  11. 7 Schools StatPeers Group 8 5 APS Feeders in Group 8 West Mesa Manzano Del Norte West Mesa Valley Garfield Jimmy Carter John Adams Kennedy McKinley Taft Wilson Valley Highland Statistical Peers for Benchmarking 11

  12. Statistical Peers Group 7 Statistical Peers Group 8 Statistical Peers Group 9 Statistical Peers Group 10 Ernie Pyle Harrison Hayes 1 Polk 1 Truman Van Buren Washington Garfield Jimmy Carter John Adams 1 Kennedy 1 McKinley 3 Taft 1 Wilson Cleveland Grant Jackson 2 Jefferson James Monroe LB Johnson 1 Taylor Desert Ridge 1 Eisenhower Hoover 1 Madison 1 Roosevelt Statistical Peers for Benchmarking • Schools with select special programs are identified 1 Special Ed. Intensive Support Program site 2 Site for Blind / Visually Impaired program 3 Site for Deaf / Hard of Hearing program 12

  13. Statistical Peers for Benchmarking Now how to use this tool? 13

  14. Blue line is Reading AMO 2007 NMSBA (5-8 MS = 42%) Beat AMO & yet below prediction Near Within Exceeds Peer Group Reading APS Predicted Solid bars show schools’ percent proficient achieved. Hairlines show predicted achievement range (95% confidence interval). 14

  15. Predicted % proficient Confidence interval Math Proficiency & Prediction SBA Middle Schools 15

  16. Red line is Math AMO2007 NMSBA (20%) Future AMOs Peer Group 9 Math APS Predicted 2007 SBA 16

  17. Schools less similar% FRPM, % ELL, etc. Peer Group 9 Math APS Predicted 2007 SBA Schools more similar% FRPM, % ELL, etc. 17

  18. Peer Group 1 Math APS Predicted 2007 SBA 18

  19. Why Use Statistical Peers for Benchmarking? • Data-driven grouping option • Increase collaboration • Share paths of success with statistical peers • Identify strategies that are effective with similar students 19

  20. Some Ways to Compare • Outcome measures • SBA, Short-cycle assessments • Graduation rate • Process indicators • Teacher collaboration time • % ICs time on essential functions • Instructional programs • Dual language • Math / Science labs 20

  21. Using the Tool • Other uses • Considering program change • Breakout groups for PD training 21

  22. Contact River Dunavin 848-8743 dunavin_r@aps.edu Research & Evaluation Team Research, Development, and Accountability Dept. Albuquerque, Public Schools 22 RDA / rDu / 0907 16

  23. Report Data Table 3 UPM: Underperforming Minorities 23

  24. Future AMOs Peer Group 1 Math APS Predicted 2007 SBA 24

  25. Future AMOs Peer Group 1 Reading APS Predicted 2007 SBA 25

  26. Future AMOs Peer Group 2 Math APS Predicted 2007 SBA 26

  27. Future AMOs Peer Group 2 Reading APS Predicted 2007 SBA 27

  28. Future AMOs Peer Group 3 Math APS Predicted 2007 SBA 28

  29. Future AMOs Peer Group 3 Reading APS Predicted 2007 SBA 29

  30. Future AMOs Peer Group 4 Math APS Predicted 2007 SBA 30

  31. Future AMOs Peer Group 4 Reading APS Predicted 2007 SBA 31

  32. Future AMOs Peer Group 5 Math APS Predicted 2007 SBA 32

  33. Future AMOs Peer Group 5 Reading APS Predicted 2007 SBA 33

  34. Future AMOs Peer Group 6 Math APS Predicted 2007 SBA 34

  35. Future AMOs Peer Group 6 Reading APS Predicted 2007 SBA 35

  36. Future AMOs Peer Group 7 Math APS Predicted 2007 SBA 36

  37. Future AMOs Peer Group 7 Reading APS Predicted 2007 SBA 37

  38. Future AMOs Peer Group 8 Math APS Predicted 2007 SBA 38

  39. Future AMOs Peer Group 8 Reading APS Predicted 2007 SBA 39

  40. Future AMOs Peer Group 9 Math APS Predicted 2007 SBA 40

  41. Future AMOs Peer Group 9 Reading APS Predicted 2007 SBA 41

  42. Future AMOs Peer Group 10 Math APS Predicted 2007 SBA 42

  43. Future AMOs Peer Group 10 Reading APS Predicted 2007 SBA 43

  44. Future AMO Peer Group 11 Math APS Predicted 2007 SBA 44

  45. Future AMOs Peer Group 11 Reading APS Predicted 2007 SBA 45

  46. Future AMOs Peer Group 12 Math APS Predicted 2007 SBA 46

  47. Future AMOs Peer Group 12 Reading APS Predicted 2007 SBA 47

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