XII–A Developing Local Data Teams: Moving Toward Data-Informed Decisionmaking

Dawn Hendricks, Virginia Department of Education
Robert Ruggiero, DaSy, AEM Corporation
Haidee Bernstein, DaSy, Westat

Data teams are groups of individuals dedicated to data inquiry and the outcomes it supports. It is important that members of a data team work well together to obtain, evaluate, and utilize highquality data to make decisions that influence services and outcomes in their locality. Guidelines for establishing effective data teams include ensuring alignment of values among team members; allowing all team members to identify their strengths; defining the purpose of the team; and valuing and honoring the implemented processes. This session will blend constructs of effective teaming with input about data teams in a Virginia preschool program that will resonate with the audience.

Complexity: Entry Level

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Developing Local Data Teams: Moving Toward Data-Informed Decisionmaking (1.67 MB)

XII–B Governing More With Less: The Pain We All Share

Charlotte Ellis, Maine Department of Education
Alex Jackl, Bardic Systems

As we all try to handle the massive surge in the number of systems, data, and interfaces we need to deal with, governance has gone from a “nice to have” to a necessity. However, our budgets often don't reflect that. In this session, the presenters will look at how to manage system governance, data governance, and procurement governance with the staff you have, leveraging private-public partnership, and collaborating with other states.

Complexity: Intermediate Level

XII–C Visualizing the P20W: A Look at Georgia's Data Dashboards

Jackie Lundberg, Dave Evans, and Jordan Dasher, Georgia Governor's Office of Student Achievement
Bob Swiggum, Georgia Department of Education

The Georgia Higher Learning and Earnings (GHLE) interactive dashboard provides earnings information for Georgia technical college and college/university graduates who work in Georgia after earning their degrees. The Georgia High School Graduate Outcomes Dashboard shows what high school graduates do after graduation, including the percentage of graduates enrolled in college/university or working, the top in-state and out-of-state colleges by enrollment, and the percentage of students who earn a credential or degree within five years. The Schools Like Mine dashboard allows users to find schools similar to their own using any two available metrics and will also display similar schools based on all characteristics. This session will explain the function and value of the GHLE dashboard for tracking and improving positive post-school outcomes.

Complexity: Entry Level

XII–D Best Practices for Naming and Defining Data

Sonya Edwards, California Department of Education

This session will feature tips and tricks for establishing data standards to maximize data quality and utility while minimizing confusion. Through interactive exercises, participants will learn about and practice strategies for developing data standardization policies and protocols. Participants will also learn about pitfalls to avoid when developing new data definitions or refining/standardizing existing ones. In this presentation, participants will learn about pitfalls to avoid when naming and defining data; steps to establishing data standards; characteristics of a good data name/definition; and strategies for maximizing data utility and minimizing confusion through data standards.

Complexity: Entry Level

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Best Practices for Naming and Defining Data Presentation (1.36 MB)
Best Practices for Naming and Defining Data Handout (28.1 KB)

XII–E The Critical Role of Education Data in Early Childhood Pay For Success Efforts

Jennifer Tschantz, Office of Special Education Programs, U.S. Department of Education
Donna Spiker and Megan Cox, SRI International

This session will provide an overview of Pay For Success (PFS), an innovative financing mechanism being used to expand early childhood programs. The types of administrative and child-level data contained in state education data systems can be used to establish that an evidence-based intervention results in positive student outcomes and these data are essential in evaluating PFS projects once implemented. Examples of PFS applications in general early childhood and early childhood special education will be presented to demonstrate the critical role of high-quality data from state education data systems in planning and evaluating PFS efforts.

Complexity: Entry Level

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XII–F Improving Communication of P20W Research to Stakeholder Audiences

Jeffrey Thayne and Vivien Chen, Washington Education Research and Data Center

This presentation will explore some strategies and pitfalls when communicating research using P20W longitudinal data. Strategies include understanding the questions of the target audience, the narrative of the research, and the needs of the stakeholders, and how this plays into every aspect of research design and presentation. Research conducted at Washington's Education Research and Data Center (ERDC) will be used to illustrate unexpected challenges when communicating research to stakeholders.

Complexity: Entry Level

XII–G Using Your State's Data to Develop and Answer Critical Questions

Courtney Petrosky, Anita Larson, and Avisia Whiteman, Minnesota Department of Education
Nancy Copa, DaSy and Common Education Data Standards (CEDS), AEM Corporation

Your state has a lot of data, but do you know how to use it to ask and answer questions about children/students, families, personnel, and programs? The Center for IDEA Early Childhood Data Systems (DaSy) has developed resources to help you form critical questions and document what elements you need to answer those questions. This session will share Minnesota's journey using its data to answer critical questions and will demonstrate the capabilities of Common Education Data Standards (CEDS) myConnect to map elements for data analysis. Learn how you can find this information and apply it to your own data system by using myConnect.

Complexity: Intermediate Level

XII–H Using Integrated Data to Connect College and Careers: Featuring the Virginia Education Wizard

Tanya Garcia, Georgetown University Center on Education and the Workforce
Chris Pfautz, Virginia Community College System

Students have a hard time navigating our complex postsecondary and workforce systems. Statewide longitudinal data systems (SLDSs) have increased data integration across sectors, but to be effective, data must become information that is accessible, digestible, and actionable. And not just for students but also for educators, advisers, administrators, and policymakers. In a new Georgetown Center report, Virginia and seven other states are profiled as having created publicly accessible tools integrating postsecondary and workforce data. The Virginia Education Wizard is a college and career advising tool other states can learn from. The presenters will share an overview of the report and do a deep dive on the Wizard.

Complexity: Entry Level

XII–I New Analysis From The Condition of Education 2017

Cris de Brey and Joel McFarland, National Center for Education Statistics

The Condition of Education 2017, a report from the National Center for Education Statistics, contains new analyses highlighting special topics in the areas of K–12, postsecondary, and workforce outcomes. One spotlight indicator explores the relationship between risk factors and academic outcomes in kindergarten through third grade. A second new indicator examines postsecondary students' persistence after three years, broken down by race/ethnicity, SAT scores, and postsecondary institutional characteristics. The last new indicator compares the disability rates and employment status by educational attainment. Join us for a discussion of these indicators and their implications for schools, local education agencies (LEAs), and state education agencies (SEAs).

Complexity: Intermediate Level

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New Analysis From The Condition of Education 2017 (7.29 MB)

XII–J Automated Flow of Teacher Effectiveness Data and On-Time Reports

John Kraman, Matt Goodlaw, Richard Trujillo, and Seana Flanagan, New Mexico Public Education Department

New Mexico's educator effectiveness system is composed of multiple measures, including student achievement growth, classroom observation, planning and professionalism, student surveys, and teacher attendance. The data flow is complex and spread over several vendors and processes. The New Mexico Public Education Department has developed a data system to collect, store, transform, and present “on-time” reports to districts and charters. The purpose of this presentation is not only to share the data system architecture and design ideas but also to discuss the roles and responsibilities of the Educator Quality, IT PM, and IT Technical teams, and how the state structured the interactions to ensure cross-functional team performance.

Complexity: Intermediate Level