Concurrent Session XII Presentations

Friday, July 19, 2013
11:30 am – 12:30 pm

XII–A: Driving Data Quality Through Data Flow

Carla Schimelfenig, Roger Petersen, and Rachel Kruse, Iowa Department of Education

The source of all data begins with the student information system. Learn in this session how Iowa transforms student-level data collected in the primary application to populate secondary applications. The reuse of district data allows for greater exposure, thus illuminating potential issues of data quality. Timely linkages between applications have resulted in higher data quality. Comparisons between collections now generate potential adjustments for auditors as well. Multiple uses from the same data source provide consistency across secondary reporting applications. Iowa’s student-level data flow will be revealed and discussed.

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XII–B: At Your Service: How States Can Support Local Education Agencies (LEAs)

Sara Kock, South Dakota Department of Education
Kamal Kumar, Otis Educational Systems, Inc.

The first data warehouses were primarily built to aid state education agencies (SEAs) with public and federal reporting requirements. Today, data warehouses must meet the reporting and analysis needs of SEA and district stakeholders. In this session, South Dakota will discuss the Student Teacher Accountability Reporting System (SD-STARS), a data warehouse that serves both the SEA and districts, including teachers. Panelists will share how they offered SD-STARS to the SEA and districts, saved districts time and resources, tackled public and federal reporting, and encouraged the use of data in hopes of improving student outcomes.

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At Your Service: How States Can Support Local Education Agencies (LEAs) (2.26 MB)

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XII–C: The Use of Statewide Longitudinal Data System (SLDS) for Addressing Complex Policy and Research Questions

Domenico Parisi, National Strategic Planning and Analysis Research Center (nSPARC), Mississippi State University

Statewide longitudinal data systems (SLDSs) are effective strategic planning tools and provide the most comprehensive data for setting up complex research designs aimed at addressing policy and research questions in a timely and cost-effective manner. Considerable investment has been made to build and implement longitudinal data systems around the country. This session will provide real examples of how to use an SLDS for strategic planning, program or institutional evaluation, policy analysis, and basic research. Examples will include questions of student absenteeism and student performance, the relationship between teacher ACT scores and student outcomes, the Head Start fade-out effect, and how SLDS can be used to predict outcomes based on third- and eighth-grade reading proficiency levels.

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XII–D: Using Predictive Analytics to Identify At-Risk Students

Vasuki Rethinam, Howard County Public School System (Maryland)

Predictive analytics or prediction models are currently popular among education leaders across the nation. Many school districts are using predictive analytics effectively to predict student performance and, more importantly, to identify students at risk. This session will discuss how district leaders, administrators, and teachers can use this information to make better decisions about deploying resources across their district, developing and evaluating intervention programs to assist students, and re-allocating resources to address problems more effectively.

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XII–E: Common Education Data Standards (CEDS) Enabling Race to the Top Assessment

Larry Fruth, SIF Association
Jill Abbott, Abbott Advisor Group

The Assessment Interoperability Framework (AIF) is being developed by technical standards communities in support of the U.S. Department of Education’s Race to the Top Assessment Program and the two consortia developing state-of-the-art online assessment capabilities for students across the country. The AIF not only supports the Race to the Top Assessment Consortia, but also focuses on the entire assessment lifecycle, enabling comprehensive interoperability for all forms of assessment and proving crucial in strengthening learning in the classroom. Come see how the AIF work is enabling interoperable content and data in both formative and summative assessment for districts and states.

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Common Education Data Standards (CEDS) Enabling Race to the Top Assessment (684 KB)

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XII–F: Colorado's Data Pipeline

Daniel Domagala and Lisa Bradley, Colorado Department of Education

With assistance from a statewide longitudinal data system (SLDS) grant, Colorado is overhauling a 20-year-old data collection system. Data Pipeline, a new system designed to efficiently capture state education data, launches in July. Learn in this session about the shift from a duplicative program-centric process to a streamlined, student-based approach. Hear lessons learned across the design, development, and pilot phases. Catch a glimpse of this custom-built, browser-based application and the associated district-support model.

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Colorado's Data Pipeline (7.48 MB)

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XII–G: The Massachusetts/Ohio Instructional Improvement System (IIS)—The Local Education Agency (LEA) Perspective

Dawn Henry, Oregon City Schools (Ohio)
Pam Rhea, Thinkgate

See a demonstration of the Thinkgate Instructional Improvement System (IIS) that was selected by Massachusetts and Ohio as a result of a joint procurement effort. Hear from local education agencies (LEAs) who were involved in the pilot as they discuss how they plan to use the system in their schools as well as how they are rolling the system out to their staff.

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XII–H: Discovering What’s Inside Mathematics Courses … and Taking the Next Step

Janis Brown, National Center for Education Statistics
Shep Roey, Westat

This session will engage states in a discussion of the findings from NCES’ Mathematics Curriculum Study. The report showed that across the country the content of Algebra I and Geometry courses varies, school course titles often overstate the content and challenge of a course, and students who took rigorous courses obtained higher NAEP mathematics scores. The findings raised questions about course titles, the impact of the Common Core State Standards on future course content, and ways to ensure student readiness for college and career. Bring your thoughts and questions for an open dialogue about the next steps to address these issues.

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XII–I: Collecting Data From District of Columbia College Access Providers: From Overcoming the Legal Hurdle to Reporting Preliminary Findings

Katie Williams and Jeff Noel, District of Columbia Office of the State Superintendent of Education

This year for the first time ever, the District of Columbia Office of the State Superintendent of Education (OSSE) entered into data-sharing agreements with a group of College Access Providers (CAPs) around the District of Columbia. In exchange for enrollment data, the OSSE provided CAPs with student-level demographic and academic performance information. This effort is the first step in a larger priority to expand coverage of college access programs and to ultimately increase the number of students in the District of Columbia who successfully complete high school and college. This session will cover the process in which the OSSE engaged to enable the collection of the new data from these nongovernmental entities and provide interested participants with the legal vehicle they needed to make this effort possible. The presenters will also share the preliminary findings from the CAP data as well as OSSE’s plans to improve and enhance the process in subsequent collections.

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XII–J: Data-Informed Decisionmaking: It Takes A City

Margie Johnson and Laura Hansen, Metropolitan Nashville Public Schools (Tennessee)

Learn how Nashville, Tennessee, comes together via Metropolitan Nashville Public Schools’ Longitudinal Educational Analytics and Decision Support System (LEADS) to support its children’s education. The Metropolitan Nashville Public School system’s data warehouse is sharing data not only within the district but also with key community stakeholders who are using the data to provide strategic supports to students. Of course, data mean little without strategic, systematic professional learning, a topic that will also be discussed in this session.

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Data-Informed Decisionmaking: It Takes A City (2.59 MB)

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