WASL Growth

1. WASL Growth WERA March 27 10:15 – 11:30 Don Schmitz: Director of Assessment Sarah Swain-Annepu: Grade 3/4 Teacher Melissa Walker: Grade 5 Teacher

2. Goal #1: Stimulate discussion and research on WASL growth.

3. Goal #2: Identify instructional practices for programs with high WASL Growth.

4. Mukilteo School District by the numbers • Students 14,485 • Number of Schools 18 • Free and Reduced 40% • TBL 16% • Ethnicity • Amer. Ind. 1.6% • Asian 14.2% • Black 5.2% • Hispanic 15.0% • White 58.7% • Classroom teachers 797

5. Accountability Models • Status • Improvement • Growth • Value-Added Goldschmidt, Pete (2005).Policymakers’ Guide to Growth Models for School Accountability: How do Accountability Models Differ? . Council of Chief State School Officers.

6. 1. Status Model • On average, how are students performing this year? Annual Target Used for Safe Harbor in AYP Year x Year x +1

7. 2. Improvement Model • On average, are students doing better this year as compared to students in the same grade last year? Improvement Year 1 Year 2

8. 3. Growth Model • How much on average, did the same students’ performance change? Growth At least two scores for each student. Year 1 Year 2

9. 4. Value-Added Model • On average, did students’ change in performance meet the growth expectation? By how much? Actual Performance Value Added Expected Performance Starting Point Year 1 Year 2

10. WASL Data(in yellow) status Grades 4-8 cohorts improvement Growth

11. Grade 4 Cohort Post WASL Pre WASL Gr. 3 Cohort 4th Gr. 4 N = 900 All statistics reported are based on the cohort of students.

12. Post WASL Pre WASL Gr. 3 Cohort 4th Gr. 4 N = 900 Grade 4 Cohort

13. Grade 4 to 8 Cohorts Grade 4 grade 5 grade 6 grade 7 grade 8 N = 4450

14. What are some issues with this approach? Each subject and grade level has different average WASL scores (different test) Classes are made up of different composition of students Achievement levels Ability levels Behavior Demographics Only one year of data

15. What are some benefits of this approach? Levels the playing field Measures gains on same students or same groups of students. Uses the measure in which we are being held accountable.

16. Four Growth Calculations 1 Diff 2 DiffAvg 3 DiffLvl 4 DiffZ

17. 5 Cohorts: grades 4 - 8 Post WASL Pre WASL 2006 Cohort 2007 N = 900 (estimate) 1 Post - Pre = Difference Score (Diff)

18. Post - Pre = Difference Score (Diff) Single student example: Pre WASL Math = 400 Post WASL Math = 410 Difference Score = +10 Diff = +10 1

19. Reading Diff Means by Grade

20. Math Diff Means by Grade

21. Cohort Sample Post WASL Pre WASL 2006 Cohort 2007 2 N = 900 (estimate) Post - Pre = Difference Score (Diff) (Post - Pre ) – District Average = Difference Score (DiffAvg)

22. (Post - Pre ) – District Average = Difference Score (DiffAvg) Single student example: Grade 3 WASL Math = 400 Grade 4 WASL Math = 410 Difference Score = +10 (Avg Diff for grade cohort = -4) DiffAvg = +14 2

23. Grade Cohort Post WASL Pre WASL 2006 Cohort 2007 3 N = 900 (estimate) Post - Pre = Difference Score (Diff) (Post - Pre ) – District Average = Difference Score (DiffAvg) (Post - Pre ) – District Average by Level = Difference Score (DiffAvgLvl)

24. Math: by pretest levels

26. (Post - Pre ) – District Average by Level = Difference Score (DiffAvgLvl) Single student example: Grade 3 WASL Math = 400 Grade 4 WASL Math = 410 Difference Score = +10 (Average Diff. for grade level 3 = +2) DiffAvgLvl = +8 3

27. Grade Cohort Post WASL Pre WASL 2006 Cohort 2007 4 N = 900 (estimate) Post - Pre = Difference Score (Diff) (Post - Pre ) – District Average = Difference Score (DiffAvg) (Post - Pre ) – District Average by Level = Difference Score (DiffAvgLvl) (Post z – Pre z ) = Difference Score (DiffZ)

28. (Post z – Pre z ) = Difference Score (DiffZ) Single student example: Z = WASL score - mean/standard deviation (mean = 0, SD = 1) Grade 3 WASL Math z score = 0.2 Grade 4 WASL Math z score = 0.3 Difference Z Score = 0.1 DiffZ = 0.1 4

29. Primary Variables Student name/ID Pre WASL Pre WASL Level Post WASL

30. Category Variables Grade School Special Education ELL F & R Teacher name Teacher experience

31. Sample Programs/Classrooms Special Education Gifted (Summit) Transitional Bilingual Free & Reduced Achievement Gap

32. Special Education n= 414 4

33. Gifted: Summit (n= 167) 4

34. Achievement Gap: Reading 1 RdgDiff (all cohorts) 4 RdgDiffZ (all cohorts)

35. Free & Reduced 4

36. MathDiff by Grades

37. Schools: MthDiff 1

38. Schools: MthDiffMSD 2

39. Schools: MthDiffLvl 3

40. Schools: MthDiffZ 4

41. Math by Pretest Levels 3

42. WASL Growth by Teacher • Illustrates the range of differences • This is not a rank order • Too many uncontrolled variables

43. Years of Experience with Diff Scores 4

44. Reading Growth 3

45. Math Growth 3

46. Goal #2: Identify instructional practices for programs with high WASL Growth

47. Odyssey Elementary

48. 2002-2003: Free/Reduced Lunch . . . . . . .55.4% Special Education . . . . . . . . .14.2% Non-English Speaking . . . . .13.3% October 2003 . . . . . . . . . . . . . 568 2006-2007: Free/Reduced Lunch . . . . . . .56.5% Special Education . . . . . . . . .11.7% Non-English Speaking . . . . .27.9% October 2006 . . . . . . . . . . . . . 709 Odyssey Elementary:

49. Our Vision: We will assure high levels of learning for all students. High behavioral and academic expectations Strong academic focus Character Education

50. What we do: • Strong Leadership • Looping & Cluster classrooms • IEP • ELL • Extended day • PLC’s