Value-Added Overview

1. Value-Added Overview August 16, 2012 Sapulpa Public Schools

2. Our Mission • The mission of Sapulpa Public Schools, in partnership with the community, is to provide a premier education to ensure that every student achieves success in a global society.

3. Sapulpa Public Schools’Self-Assessment

4. Learning Targets • Understand why value-added analysis provides a more complete picture of school and teacher effectiveness. • Understand how harnessing the power of two, achievement and progress, provides a more robust picture of school improvement. • Develop a conceptual understanding of growth metrics

5. National Landscape “Education is no longer a pathway to opportunity and success. It is a prerequisite for success.” -President Barack Obama, March 2009

6. National Landscape No Child Left Behind (NCLB) has brought an increased focus on student achievement results for schools, school systems and specific groups of students within schools.

7. National Landscape “With increased accountability, American schools and the people who work in them are being asked to do something new—to engage in systemic, continuous improvement in the quality of the educational experience of students and to subject themselves to the discipline of measuring their success by the metric of students’ academic performance.” -Richard Elmore, Bridging the Gap Between Standards and Achievement

8. National Landscape Across the country, growth models are helping schools identify strengths, challenges and opportunities throughout the system. Growth analysis brings a new and critically important kind of diagnostic information to allow districts to be strategic and focused in their decision-making.

9. National Landscape For the first time in the history of American education, the definition of “great” teachers is grounded in the students’ academic growth, not just student achievement. The difference is subtle but extremely important.

10. Let’s Consider… • What are some ways that we determine our effectiveness as teachers? • Are some ways more insightful to our professional learning?

11. Audience Share • Teacher observation • Student growth • Classroom mgmt. • Student engagement • Student productions-produce the language • Analyze the data (achievement and benchmark) • Scaffolding information/differentiated instruction • Passion of the teacher • Parent feedback • Student independence • Student feedback • Daily work • Labs • Questions students ask • All students involved • Student attitudes • Attendance • Providing a healthy environment • Teacher knowledge of students

12. Audience Share

13. The Right Measures All measures should inform practice and lead to improvement for students. Multiple measures should clarify, not confuse. Multiple measures are not necessarily “better.” Less is more, sometimes. Important to measure what is important.

14. Using the Measures Correctly Don’t just admire the data. Harness the power of data for improvement, not judgment. Convert data to information. Respond to the data. Don’t react.

15. What is value-added analysis? • Value-added models measure the influence of schools or teachers on the academic growth rates of students. • Value-added analysis compares the change in achievement of a group of students from one year to the next, to an expected amount of change, based on their prior achievement history and other potential influences.

16. Stair Step Expectations • In a perfect world: • Students start at the same place. • Students progress at the same pace. • Achievement test scores are enough to show growth.

17. Differentiated Reality • In reality: • Students start at different places. • Students progress at different rates. • We need more than scores on a single test to show a school’s effectiveness.

18. Why use value-added analysis? Using value-added analysis, along with other data allows us to separate… what we think is happening from what is actually happening.

19. What do you see?

20. Take a second look.

21. Harnessing the Power of Data for Improvement To do this we need: • The right questions • The rightdata • The knowledge to interpret these data • The wisdom to respond (not react) and apply strategies for school improvement

22. Setting the Stage: The Power of Two

23. Achievement plus Growth Measures =A Clearer Picture of Student Outcomes Achievement Measures a student’s performance at a point in time on a single test in a single subject Compares to a standard (e.g., proficiency) Important to post-secondary opportunities (GPA, ACT) The Power of Two

24. Achievement plus Growth Measures=A Clearer Picture of Student Outcomes Growth Measures the student’s progress between two points in time Uses student’s own prior performance to predict future performance May factor in student background characteristics Uses multiple data points (including student demographics) that relate to student performance to increase precision Measures the effect a district, school, grade-level, classroom or teacher has on growth of student The Power of Two

25. The Power of Two:Achievement & Progress • How do value-added measures support what we know about schools? High Progress Low Achievement High Progress High Achievement • SchoolA • SchoolJ • SchoolH • SchoolE • SchoolC Progress One Year’s Growth Standard • SchoolK • SchoolG • SchoolF • SchoolB • SchoolD Low Progress Low Achievement Low Progress High Achievement Achievement Test Results

26. The Power of Two:Achievement & Progress Leading High Progress Low Achievement High Progress High Achievement • SchoolA • SchoolJ • SchoolH • SchoolE • SchoolC Progress One Year’s Growth Standard • SchoolK • SchoolG • SchoolF • SchoolB • SchoolD Low Progress Low Achievement Low Progress High Achievement Achievement Test Results

27. The Power of Two:Achievement & Progress Learning High Progress Low Achievement High Progress High Achievement • SchoolA • SchoolJ • SchoolH • SchoolE • SchoolC Progress One Year’s Growth Standard • SchoolK • SchoolG • SchoolF • SchoolB • SchoolD Low Progress Low Achievement Low Progress High Achievement Achievement Test Results

28. The Power of Two:Achievement & Progress Losing Ground High Progress Low Achievement High Progress High Achievement • SchoolA • SchoolJ • SchoolH • SchoolE • SchoolC Progress One Year’s Growth Standard • SchoolK • SchoolG • SchoolF • SchoolB • SchoolD Low Progress Low Achievement Low Progress High Achievement Achievement Test Results

29. The Power of Two:Achievement & Progress Lucky High Progress Low Achievement High Progress High Achievement • SchoolA • SchoolJ • SchoolH • SchoolE • SchoolC Progress One Year’s Growth Standard • SchoolK • SchoolG • SchoolF • SchoolB • SchoolD Low Progress Low Achievement Low Progress High Achievement Achievement Test Results

30. Pause and Reflect • Where do you think your school is? • Where would you like to be? • What strategies can you embrace now to get there?

31. Although it appears that Gardener B was more effective in attaining a taller tree, it does not tell the whole story. • The gardeners’ oak trees are 4 years old. • We need to find the starting height for each tree in order to more fairly evaluate each gardener’s performance during the past year. • Both trees were much shorter last year. • Oak Tree A grew by 14 inches and Oak Tree B grew by 20 inches. 72 in. Gardener B Gardener A +20 in. +14 in. 61 in. 52 in. 47 in. Oak A Age 4 (Today) Oak A Age 3 (1 year ago) Oak B Age 3 (1 year ago) Oak B Age 4 (Today) This is analogous to a Simple Growth Model

32. A Conceptual Analogy Achievement Model Simple Growth Model Value-Added Model

33. We begin by understanding what attributed to the growth of the gardeners’ trees. • For the past year, the gardeners have been tending to their oak trees, trying to maximize the height of the trees. • Each gardener used a variety of strategies to help their own trees grow. • After one year of implementing their strategies, one of Gardener A’s tree grew to 61 inches tall and one of Gardener B’s trees grew to 72 inches tall. 72 in. Gardener B Gardener A 61 in. This is analogous to an Achievement Model

34. We still do not know how much of this growth was due to the strategies used by each gardener. • We need a more accurate estimate. • We examine all oaks in each respective area to find the average height increase for these trees. • We also take into consideration the impact of three environmental factors: Rainfall, Soil Richness, and Temperature. Gardener B Gardener A Low High

35. Now it’s time to use our data to make a more accurate prediction for the expected height of oak trees in this area. Based on data for all oak trees in the region: • The average increase in oak tree height was 20 inches during the past year. • However, each tree was exposed to different levels of rainfall, temperature and soil richness. • Therefore, we must adjust the average height during the past year to compensate for these environmental factors. 74 in. 72 in. Gardener B Gardener A 61 in. 59 in. 22 in. 12 in. +52 in. +47 in. +20 Average +20 Average - 5 for Rainfall + 3 for Rainfall + 2 for Soil - 3 for Soil + 5 for Temp - 8 for Temp _________ +22 inches During the year _________ +12 inches During the year

36. Finally, we compare the actual height of each tree to our prediction. • Our predicted heights for tree A and B are 59 and 74 inches respectively. • Oak tree A’s actual height of 61 inches is 2 inches more than we predicted. • We attribute this above-average result to the effect of Gardener A. • Oak tree B’s actual height of 72 inches is 2 inches less than we predicted. • We attribute this below-average result to the effect of Gardener B. -2 74 in. 72 in. Gardener B Gardener A +2 61 in. 59 in. This is analogous to a Value-Added Model Predicted Oak A Predicted Oak B Actual Oak A Actual Oak B

37. Apply this method to all trees under each gardener’s care. • This information can be used to calculate the height for each tree today if it were being cared for by an average gardener in this area. • Now, who is the more effective gardener? Avg. = -4 in. Avg. = +5 in. Gardener B Gardener A Predicted Oak B Actual Oak B Predicted Oak A Actual Oak A

38. How Does This Analogy Relate to Value-Added in the Education Context?

39. Reflection • Why is it important to measure both achievement and progress? • What are the challenges of identifying our most effective practices through a single lens of an achievement measure? • How may the use of value added measures inform our efforts to identify and replicate our most effective practices?

40. The Value-Added Research Center (VARC) Model • School Level Results • Teacher Level Results

41. Value-Added Color Scheme on Reports

42. Which grade-level team should be prioritized?

43. Value-Added Analysis: Actual minus Predicted Value-Added Above Prediction Value-Added AtPrediction Value-Added Below Predicted

44. Prior Data Points Used to Predict: • Using the data from the Oklahoma Core Curriculum Test (OCCT), in reading and math… • A prior reading achievement level can be predictive of reading achievement. • e.g., 7th grade reading predicts 8th grade reading • A prior math achievement level can be predictive of math achievement. • It is also possible that a prior reading test can predict math and vice versa.

45. Culture Matters • For many of us, examining data can be very personal. • The school value-added report may be the first time we look into the mirror and reflect upon the impact of our practices. • A supportive and collaborative culture fosters using the data to improve our practices in a positive and productive manner.

46. Closing Questions • Think about your school’s culture. How would we assess our readiness to collaborate around our data for the purposes of improved practice? • What are some ways that we can nurture a positive school culture for using value-added data to improve practice?

47. Check for Understanding Please complete the 3–2–1 Exit Ticket before leaving today. 3 Ways value-added data can improve your school and/or classroom. 2 Things you would like to further explore. 1 Takeaway you gleaned from this presentation.

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