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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, 2007 Elizabeth Laird, Data Quality Campaign. Framing thoughts…. Without data, you are just another person with an opinion…..
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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, 2007 Elizabeth 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 Elements • Unique statewide student identifier • Student-level enrollment, demographic and program participation information • Ability to match individual students’ test records from year to year to measure growth • Information on untested students • Teacher identifier system with ability match teachers to students • Student-level transcript information, including information on courses completed and grades earned • Student-level college readiness test scores • Student-level graduation and dropout data • Ability to match student records between the Pre-K-12 and post-secondary systems • State data audit system assessing data quality, validity, and reliability
Data Quality Campaign isBuilding 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 toimprove 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, 2006 • Using 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.
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.
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 databases • eSchoolPLUS (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.
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 Associate Elizabeth@DataQualityCampaign.org 512.320.1817