State of the Nation: How Schools, Districts, and States

Are Using Longitudinal Data

Using Data to Improve Instruction: Building on Models that Work

September 14, 2007Elizabeth Laird, Data Quality Campaign

Framing thoughts…

Without data, you are just another person with an opinion…..

Culture Change underway in Education Community:

View data not as a hammer, but as a

flashlight.

The Power of Longitudinal Data

Longitudinal Data — data gathered on the same student from year to year — makes it possible to:

Follow individual student academic growth

Determine the value-added of specific programs

Identify consistently high-performing schools/classroom/systems worthy of study

10 Essential Elements1. Unique statewide student identifier 2. Student-level enrollment, demographic and program participation

information 3. Ability to match individual students’ test records from year to year to

measure growth 4. Information on untested students 5. Teacher identifier system with ability match teachers to students 6. Student-level transcript information, including information on

courses completed and grades earned 7. Student-level college readiness test scores 8. Student-level graduation and dropout data 9. Ability to match student records between the Pre-K-12 and post-

secondary systems 10. State data audit system assessing data quality, validity, and

reliability

State of the State Data Systems

Data Quality Campaign is Building Support and Political Will to:

Fully develop high-quality longitudinal data systems in every state by 2009

Increase understanding and promote the valuable uses of longitudinal and financial data to improve student achievement

Promote, develop, and use common data standards and efficient data transfer and exchange

Quarterly Issue Meetings

Discuss “hot” policy topics and how they are informed by better data.

Meetings are held in Washington DC, but are also available through interactive web casts.

Each meeting is accompanied with an Issue Brief.

Hosted 6 quarterly issue meetings.

Quarterly Issue Meetings

September 25, 2006Using Data in the Central Office and the

Classroom to Improve Student Achievement March 12, 2007

Connecting Teacher and Student Data: Benefits, Challenges, and Lessons Learned

Disclaimer!

Don’t expect any surprises Summarize general themes DQC has

heard and how schools, districts, and states are addressing them

Interested in hearing from you all how our points relate to what you are experiencing

Thanks to DQC Panelists Using Data, Sept. 25, 2006

Amy Andres, Ohio Department of Education Ed Hedgepeth, Knox County Schools Holly Fisackerly, Aldine ISD

Connecting Teacher and Student ID, March 12, 2007 Jacki Paone, Alliance for Quality Teaching Audrey Noble, University of Delaware Robin Taylor, Delaware Department of Education Katie Peters-Crosby, Miami East Elementary School,

Ohio

Effective Longitudinal Data Use- Overview Establish a culture of data use Design the data system for the end user Provide ongoing professional development

to education stakeholders at all levels Administer longitudinal data systems at

the state level

Establish a culture of data use

Culture change is underway in the education community “View data as a flashlight, not a hammer.”

TRUST, TRUST, TRUST Involve ALL stakeholders from the beginning

when building and using data systems Examples

Ohio House Bill (HB) 3 Colorado Senate Bill (SB) 140

Ohio House Bill (HB) 3

Passed with bipartisan support in August 2003

Requires Ohio include value-added progress measure as an official metric in Ohio’s education accountability system in 2007-2008

Value-Added reports provided to all Ohio districts

Ohio’s Value-Added Rollout

“Evolution, not a Revolution.” HB 3 started as a voluntary pilot program in 42

districts Created groundswell of demand for this

information Ohio’s teachers’ unions, education associations,

educators and business and community leaders led the passage of this legislation

Colorado- Senate Bill (SB) 140

Passed in April 2007 Calls for the creation of a commission

whose duties include developing a unique teacher ID protocol and a method for integrating the identifier into

current and emerging databases.

Colorado- Journey to a Teacher ID

2005- Alliance for Quality Teaching began exploring creating a unique teacher ID

2006- legislation to establish a unique teacher ID was blocked due to mistrust

Summer 2006- Hosted 4 broadly attended meetings to: examine lessons learned from other states that have

developed similar systems; address concerns about state capacity, resources and

use of data; and develop a set of recommendations.

Professional Development Programs Provide regular, system-wide training for all

educators Offer multiple opportunities for professional

development in addition to system-wide trainings Train the Trainers Examples

Knoxville County Schools Ohio Value-Added Rollout

Knox County Schools- TVAAS

Tennessee Value-Added Assessment System (TVAAS) tracks student academic growth over time

Massive, longitudinal database established in 1992 that links students and student outcomes to schools and systems in which they are enrolled teachers to whom they are assigned

Goal: identify and learn from those teachers whose students perform better than this expected level.

Knox County Schools- Data Training and Support

Ohio Value-Added Rollout

2002- Battelle for Kids piloted providing value-added reports on schools and districts, in 42 voluntary Ohio districts.

2003- Ohio House Bill (HB) 3 was passed, which required incorporating value-added assessment into Ohio’s accountability system.

More than 100 Ohio school districts participate in pilot — representing approximately 30 percent of the state’s students.

Ohio Value-Added Training

Regional Value-Added Specialists (RVAS) 12 school improvement regions in Ohio 80 RVAS have made a two-year commitment to learn

more about value-added analysis’ uses and benefits and to train others.

District Value-Added Specialists (DVAS) RVAS are training 1,200 DVAS to understand,

interpret and use value-added information. By the 2007-2008 school year, approximately

1,400 individuals will be trained in value-added.

Data Use Drives Data System

Historically, education has been data rich but information poor

Data only become information if they are used Design with the end user AND purpose in mind Reporting and analysis just as vital to data

systems infrastructure Examples

Aldine Independent School District Delaware Correlates of Achievement

Aldine Independent School District

Aldine ISD was selected as a district finalist for the Broad Urban Prize Award in both 2004 and 2005.

Contributing factor is the district’s use of data by disaggregating state, local and formative assessment

information on students; mandating benchmark assessments; and creating teacher plans based on students’ past and

current achievement.

Aldine ISD- Timely, User-friendly Data Access Custom data system that provides quick, easy

access to longitudinal results from state assessments, district-developed formative assessments and benchmark assessments. “The information is broken down in periods. It allows

you to see that maybe you do better in the morning and allows you to rethink your process,” Teacher in Aldine ISD.

District monitors whole-school performance every six weeks.

Aldine- Immediate disaggregation and item analysis

Delaware’s Multiple Data Systems, Two Reporting Features 2006- Delaware began linking teacher and

student databases Unique teacher ID provides the link

between two important databaseseSchoolPLUS (eSP)Delaware Educator Data System (DEEDS)

Delaware- Two Reporting Systems Correlates of Achievement- Goal

use data for school improvement close the achievement gap

Automate NCLB reporting on highly qualified teachers- Goal Improve data quality by monitoring missing data

elements Enable disaggregated analyses such as looking at the

highly qualified teacher data by poverty level at the school or student level teacher experience minority status of the school or the students.

Longitudinal Statewide Data

Much progress has been made, but still more work to be done

Sometimes large district data systems more sophisticated than state data systems

Complement statewide assessment data with local formative assessment data

Example Ohio’s D3A2 Initiative

Ohio- Data Driven Decisions for Academic Achievement (D3A2) Funded in part by the U.S. Department of

Education’s Institute of Education Sciences three year, $5.7 million grant and $1.2 million from the Ohio Department of Education

Purpose: give Ohio educators access to timely longitudinal data and educational resources aligned to Ohio’s academic content standards

Conducted several teacher focus groups to ensure data met users’ needs

Ohio- D3A2

School districts can load data into a secure state-supported data warehouse with up to three years of local and statewide assessment data at the classroom item-analysis level Ability to analyze results for both local and state exams if the

district chooses to submit these data. Help teachers identify areas for improvement and links to

aligned electronic educational content resources. A teacher is able to view a student’s achievement results by

standard and then click through to content resources focused on improving student success on that standard.

Ohio- Benchmarking with Resources

Roadmap to using data

1. Advocate for the 10 Essential Elements of a State Longitudinal Data Systems

2. Support leadership efforts to provide timely and user-friendly access to longitudinal data

3. Encourage a culture change where teachers and principals use data as a school improvement tool

4. Participate and provide professional development on using data to improve student achievement

5. Seek and share best practices as identified through longitudinal data analysis

6. Incorporate data into the education process to improve student achievement

Send feedback/ideas to the DQC:

www.DataQualityCampaign.org

Elizabeth Laird,

DQC Research AssociateElizabeth@DataQualityCampaign.org

512.320.1817