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

Value-Added Overview

Sapulpa Public Schools

August 16, 2012

Copyright, 2012. Battelle for Kids.

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.

Sapulpa Public Schools’Self-Assessment

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

“Education is no longer a pathway to opportunity and success. It is a prerequisite for success.”

-President Barack Obama, March 2009

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.

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

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.

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.

National Landscape

Let’s Consider…

What are some ways that we determine our effectiveness as teachers?

Are some ways more insightful to our professional learning?

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

Audience Share

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.

The Right Measures

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.

Using the Measures Correctly

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.

What is value-added analysis?

In a perfect world: Students start at the same place. Students progress at the same pace. Achievement test scores are enough to

show growth.

Stair Step Expectations

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.

Differentiated Reality

Why use value-added analysis?

Using value-added analysis, along with other data allows us to separate…

what we think is happeningfrom

what is actually happening.

What do you see?

Take a second look.

To do this we need: The right questions The right data The knowledge to interpret these data The wisdom to respond (not react) and apply

strategies for school improvement

Harnessing the Power of Data for Improvement

Setting the Stage: The Power of Two

The Power of Two

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,

The Power of Two

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

How do value-added measures support what we know about schools?

The Power of Two:Achievement & Progress

ear’

AchievementTest Results

Standard

Low ProgressLow Achievement

Low ProgressHigh Achievement

High ProgressLow Achievement

High ProgressHigh Achievement

• School A

• School B

• School C

• School D

• School E

• School F

• School H

• School K

• School G

• School J

ear’

Standard

• School A

• School B

• School C

• School D

• School E

• School F

• School H

• School K

• School G

• School J

Leading

ear’

Standard

• School A

• School B

• School C

• School D

• School E

• School F

• School H

• School K

• School G

• School J

Learning

ear’

Standard

• School A

• School B

• School C

• School D

• School E

• School F

• School H

• School K

• School G

• School J

Losing Ground

ear’

Standard

• School A

• School B

• School C

• School D

• School E

• School F

• School H

• School K

• School G

• School J

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?

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.

Gardener AGardener B61 in.

Oak AAge 4

(Today)

72 in.

Oak BAge 4

(Today)

Oak AAge 3

(1 year ago)

47 in.

Oak BAge 3

(1 year ago)

52 in.

Although it appears that Gardener B was more effective in attaining a taller tree, it does not tell the whole story.

+14 in.

+20 in.

This is analogous to a Simple Growth Model

Achievement ModelSimple Growth ModelValue-Added Model

A Conceptual Analogy

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.

Gardener A Gardener B

61 in.

72 in.

We begin by understanding what attributed to the growth of the gardeners’ trees.

This is analogous to an Achievement Model

Low High

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.

+20 Average+20 Average

+ 3 for Rainfall

- 3 for Soil + 2 for Soil

- 8 for Temp + 5 for Temp_________+12 inchesDuring the year

_________+22 inches During the year

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.

+47 in. +52 in.

- 5 for Rainfall

Based on data for all oak trees in the region:

Now it’s time to use our data to make a more accurate prediction for the expected height of oak trees in this area.

59 in.12 in.

74 in.

22 in.61 in.

72 in.

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.

Finally, we compare the actual height of each tree to our prediction.

PredictedOak A

PredictedOak B

ActualOak A

ActualOak B

59 in.

74 in.Gardener A Gardener B

61 in.

72 in.+2

This is analogous to a Value-Added Model

PredictedOak B

ActualOak B

Gardener A

Avg. = -4 in.

PredictedOak A

ActualOak A

Avg. = +5 in.

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?

Gardener B

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

Oak Tree Analogy Value-added in Education

What are we looking at? • Gardeners • Districts• Schools• Grade levels• Classrooms• Programs and

Interventions

What are we using to measure success?

• Relative height improvement in inches

• Relative improvement on standardized test scores

Sample • Single oak tree • Groups of students

Control factors • Rainfall• Soil richness• Temperature

• Students’ prior test performance (usually most significant predictor)

• Other demographic characteristics (grade level, gender, SWD, ELL status, IEP status, mobility, etc.)

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?

The Value-Added Research Center (VARC) Model

School Level Results Teacher Level Results

Value-Added Color Scheme on Reports

Which grade-level team should be prioritized?

Value-Added Analysis: Actual minus Predicted

Value-Added Above Prediction

Value-Added Below Predicted

Value-Added At Prediction

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.

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.

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?

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.

www.BattelleforKids.orghttp://twitter.com/BattelleforKids

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

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