Concurrent Session XI Presentations
Friday, August 1, 2014
10:15 am – 11:15 am
XI–A: Lessons Learned From One of the Largest PK–12
Unique Identifier System Implementations
Sharon Gaston and Mark Gentzel, Texas Education Agency
Juan Guerrero, eScholar LLC
One of the cornerstones of the Texas Student Data System is the implementation of eScholar Uniq-
ID, which provides a unique identifier for all staff and students in the state. During this session,
representatives from the Texas Education Agency and eScholar will discuss the benefits, transition
process, and the lessons learned from implementation, training, and deployment of a statewide
identifier system for more than 14 million active/historical records of students and staff members.
XI–B: The Uses of School Health Data in DC
Ifedolapo Bamikole, UDistrict of Columbia Office of the State Superintendent of Education
Innovative health policy and programs such as the Healthy Schools Act are part of aggressive
public health actions that DC’s leadership has taken in schools to address health issues. This has
resulted in DC leading the nation in free school breakfast and being well on its way to better
health and academic outcomes for DC students. With multiple implementation efforts, progress
monitoring provides a unique data challenge in assessing outcomes alongside test scores, the
Youth Risk Behavior Survey, School Health Profiles, and health-related information in the statewide
longitudinal data system (SLDS). We plan to share how we utilize these multiple sources of data
in evaluation.
XI–C: My School Data—Making a Difference
Through Data in Washington Schools
Carrie Retzer and Ken Mock, Washington School Information Processing Cooperative (WSIPC)
Washington School Information Processing Cooperative represents 295 districts in Washington
State. To assist our districts with their data needs, we’ve developed a product called “My School
Data,” powered by our longitudinal data warehouse. This data warehouse allows My School Data
to show the history of students, regardless of which district in our state they have attended.
In this session we will show how different “views” of data, including an Early Warning System
for districts, schools, teachers, and students, can provide answers to educators’ questions. By
knowing more about students, we can better target programs and interventions to help students
be more successful.
XI–D: Research Engine—Florida’s External
Research Request Application
Andre Smith, Florida Department of Education
Florida’s Department of Education (FLDOE) is known as a national leader for its education data
system. The system contains comprehensive data, spanning from prekindergarten to postsecondary
education and workforce experiences. Built in 2003, the State Longitudinal Education Data System
(SLDS) allows business and public users to request data dating from the early 1990s. These
data are used in the development of comprehensive reports, analysis, and research pertaining
to students within the Florida education system for the length of his or her learning career and
beyond. This session will provide an overview of the FLDOE new user-friendly, web-based research engine. Using the research engine, researchers are now able to systematically navigate through
the data request process, monitor their status, and request anonymous student-level data from
the department.
XI–E: Who Moved My EDEN Queries: How to Make the Change From Manual Processes
Joseph Cowan,
Pennsylvania Department of Education
John Pagnotta,
eScholar LLC
During the past three-plus years, the Pennsylvania Department of Education (PDE) has teamed
with eScholar to use the data collected in the Pennsylvania Information Management System
(PIMS), PDE’s statewide longitudinal data system (SLDS) data warehouse, to simplify and automate
EDEN/EDFacts reporting. This session will cover the technologies used and the processes enacted
to make this project successful.
Download Zipped PowerPoint Presentation
XI–F: Using Longitudinal Data to Guide Successful
Student Transitions to Postsecondary Education
David Reeg, Minnesota Department of Education
As postsecondary education becomes increasingly important for the success of today’s students,
longitudinal data linking K–12 and postsecondary education is essential for K–12 educational
practices. Minnesota’s Statewide Longitudinal Education Data System (SLEDS) provides easy
access to school-specific information about student choices and success in transitions from K–12
to higher education. It provides critical evidence for evaluating the effectiveness of programs and
designing targeted improvement strategies, particularly related to career and college readiness.
We will demonstrate SLEDS and show you how to build the reports schools and policymakers
want. View the power of this analytic tool to strengthen decisionmaking.
Download Zipped PowerPoint Presentation:
XI–G: Ensuring Data Quality for Value-Added Measures
Mary Wolfson, Pittsburgh Public Schools (Pennsylvania)
Brian Gill and Matthew Johnson, Mathematica Policy Research
Since 2010, Pittsburgh Public Schools has worked collaboratively with Mathematica Policy
Research to implement high-quality, value-added measures (VAMs) for teachers, teams, and
schools. Although there is extensive research on the statistical characteristics of VAMs, districts
and states have far less guidance about how to ensure the integrity of the underlying data—
which is essential for the validity of the VAMs and their credibility in the eyes of educators. This
session will describe the data assurance process implemented in Pittsburgh, including establishing
accurate teacher-student data linkages, providing an opportunity for appeals, and implementing
revisions based on validated appeals.
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XI–H: New Mexico’s “Enchanting” Evolution in Longitudinal Data Collection (CANCELLED)
Kathryn Cleary, New Mexico Public Education Department
Figen Bilir, eScholar LLC
In partnership, the New Mexico Public Education Agency (NMPED) and eScholar have worked
on several statewide data initiatives, including implementing a district-facing data warehouse,
establishing unique identifiers for students, and applying data-quality solutions. NMPED will
discuss the progress it has made with its statewide data collections using a commercial, off-the-shelf,
and standards-aligned solution; enabling data collection from such diverse domains such as
student, staff, and transportation; and the agency’s evolution of data reporting. Participants will
learn how NMPED was able to achieve these accomplishments without support from any Race to
the Top (RTTT) or statewide longitudinal data system (SLDS) grants.
XI–I: Can Strategic Analytics Improve High School Graduation Rates in DC Schools?
Celine Fejeran and Jeffrey Noel, District of Columbia Office of the State Superintendent of Education
Steve Cartwright, Tembo, Inc.
This session will explore the results from an unprecedented, year-long partnership among
Washington, DC, education agencies, across traditional and charter schools, to study the high
school outcomes of more than 10,000 public school students and create an enduring set of
citywide strategies to increase secondary graduation rates. Discussants will share the project’s
analytic roadmap, review the most compelling findings from their research, and discuss how the
data are being used by school and district leaders to support students with varying levels of need
through the completion of high school. Key analyses include a predictive, early warning model of
high school completion; individual measures of schools’ “graduation value-added”; and a latent
class cluster analysis of high school students’ disengagement patterns.
XI–J: Equity, Inclusion, and Opportunity: Addressing Success Gaps in Our Schools
Tom Munk, Westat
This session introduces a research-based guidance document and self-assessment rubric designed
by the Office of Special Education Program’s (OSEP) Disproportionality Priority Team to help districts
and schools identify the root causes of “success gaps” (in, for example, test scores, suspension
or graduation rates, or course credits) for some groups of students, thereby helping schools to
improve and equalize results for all students. These tools will be particularly helpful to districts
and schools that have been selected for attention by states because of identified success gaps.
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