Using State Measures of Student Growth to Inform Local Practice (or, “Organic Isn’t Just for Veggies!”) June, 2009

Session Learning Objectives 1. Steps to go from data to student-level action-item 2. How and where local data fits in 3. How data quality and data use are related

The Value of Buy-In in Arizona 1. Process was very organic, from both the top down and the bottom up (with a little fertilizer ) 2. Year-end state data was only good for the beginning of the following year – we are creating two types of “check point” that schools are excited about 3. Quality means the data answers the questions you need, and you trust it – teachers must feel this too!

Damians Q1. What are the steps by which large scale assessment data (i.e., raw numbers) get translated into actions effecting the education of students?

Our Process Was Very Organic and Grass-Roots 1. Good access to data for value-added research from previous positive relationships • Past relationships/credibility • Political alignment • Collaboration with authorizer • Participation in federal grant

Used the growth percentile data to create a best practices report
Highlighted how the high-growth schools got where they are
Focused on providing a “road-map” to other schools to follow

Our Process Was Very Organic and Grass-Roots 2. National and local partners focused on understanding the “quality” landscape • Building Charter School Quality grant, we were approached by CO and learned about Damian’s work in growth percentiles • Led to Arizona State Board for Charter Schools to redefine quality • Led to state policymakers taking notice

Our Process Was Very Organic and Grass-Roots 3. Used the growth percentile data to create a best practices report • Highlighted how the high-growth schools got where they are • Focused on providing a “road-map” to other schools to follow

Our Process Was Very Organic and Grass-Roots 4. During research, vetted growth percentile concept with schools and learned the best ways to explain it • Schools loved it • Saw credit for growth, not starting point • Started calling to see their own data

Our Process Was Very Organic and Grass-Roots 5. One finding was about the importance of data- driven decision-making • “A-ha” moment for us • Realized that growth percentiles could take assessment from “end of year autopsy” to “pre-year and mid-year diagnosis.”

Our Process Was Very Organic and Grass-Roots 6. Became a key talking point for all of our management team • Goal was to change the definition of quality in the state to “individual student level growth” and promote “growth to standard” instead of “one year’s growth.” • We began to vet these ideas with state officials, districts, and our schools.

Our Process Was Very Organic and Grass-Roots 7. Meanwhile, we developed and marketed Best Practice workshops • Data-driven decision-making • Professional Learning Communities • Saw the growth percentile idea really appeal to them • Began to focus on how to develop tools for teachers to use it more. • Led to….

Working on Three Types of “Check Point” (that schools are excited about) 1. Beginning of year check on growth based on end- of-year AIMS tests • Damian’s cool student level graphs • Class-room level data for differentiated instruction

Damian’s Q2. With regard to your answer to question 1: How/where do local data (e.g., interim assessments, classroom observations) fit in?

Working on Three Types of “Check Point” (that schools are excited about) 2. Online interim assessment in December • Produce mid-point growth percentiles • Drive instructional decisions between January and AIMS in March

Damian’s Q2. With regard to your answer to question 1: How/where do local data (e.g., interim assessments, classroom observations) fit in?

Working on Three Types of “Check Point” (that schools are excited about) 3. Online formative assessment tool tied into PLC concept • Test bank/test building • Analysis and reporting • Professional development and communication • Goal is to build teacher comfort and capacity

Damian’s Q2. With regard to your answer to question 1: How/where do local data (e.g., interim assessments, classroom observations) fit in?

Quality means… 1. Data answers the questions you need (i.e. you can USE it) • Has policy relevance • Has classroom relevance • Teachers can quickly understand it

Damians Q3. Thinking of data broadly (large scale, small scale, ...), how are data quality and data use related.

Quality means… 2. You trust the data • Reliable (would get same results again) • Valid (measures what you want to measure) • Transparent (we can see where the data came from and how the results were created)

Damian’s Q2. With regard to your answer to question 1: How/where do local data (e.g., interim assessments, classroom observations) fit in?

Final Thoughts 1. Need to treat the whole process like a change management issue 2. The state/school feedback loop is critical 3. It’s All about relationships 4. It’s a GREAT time to be in education policy!

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Using State Measures of Student Growth to Inform Local Practice — CCSSO, June 2009.

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