Lack of appropriate academic preparation is a major reason why students do not attend college. To address this problem, the University of California developed the Transcript Evaluation Service (TES), a set of data tools that offers high school students, counselors, and administrators information on whether students are meeting college admissions requirements. Presenters demonstrated the data tools and highlighted their use in one school district serving a high percentage of disadvantaged students. As states incorporate transcripts into their data systems, TES is an example of how these data can be leveraged to improve student transition to college.

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Using Transcripts to Improve College Readiness: A Secondary/Postsecondary Partnership (1.8 MB)

Sessions in Data Use/Data Standards track:

I-C, I-D, I-E, II-A, II-C, III-C, IV-C, IV-H, V-C, V-H, VI-C, VII-A, VII-C, VIII-C, VIII-H, IX-A, IX-C, IX-C, IX-F, IX-H, X-A, X-C, X-F, XI-A, XI-D, XII-C, XII-D

Presenters discussed how Wyoming began the process of developing a statewide Schools Interoperability Framework (SIF) infrastructure to support vertical reporting and horizontal interoperability for its districts. They explained the intricacies of a SIF project of this magnitude and how to tie it to an existing Oracle database system. They explained how they worked with their contractors to create a state reporting system that communicates with a state SIF agent and is then parsed into our existing Oracle database. They covered how they used the horizontal interoperability of SIF to entice the districts to participate and how by the fourth year of the project they had no outlier districts. In Wyoming, all 48 school districts are SIF districts, some at more advanced stages than others, but all working on state reporting and most highly invested in horizontal SIF as well. They also briefly touched on the impact this has had on other projects and on data driven decision making for their state.

Sessions in Schools Interoperability Framework (SIF) track:

I-B, II-B, III-B, IV-B, V-B, VI-B, VII-B, VIII-B, IX-B

The California School Nurses Organization developed a tool for school nurses to collect and report data regarding chronic illness and related health services. These data have been used by some school districts to measure the quantity and intensity of school nursing services. The data have been used by decision makers in the state legislature and other organizations to quantify issues that affect the health, safety, and academic success of students. Data representing a subset of 1,796,735 of 6.2 million students will be reported. Incidence of diabetes, anaphylactic allergies, seizure disorders, asthma, and other conditions will be reported.

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Quantifying Issues That Affect the Health, Safety, and Academic Success of Students (2.6 MB)

Sessions in Data Use/Data Standards track:

I-C, I-D, I-E, II-A, II-C, III-C, IV-C, IV-H, V-C, V-H, VI-C, VII-A, VII-C, VIII-C, VIII-H, IX-A, IX-C, IX-F, IX-H, X-A, X-C, X-F, XI-A, XI-D, XII-C, XII-D

Having access to high quality student-teacher linkages is required for many of the high profile projects such as classroom-level value-added analysis, randomized control trials, and teacher incentive fund (TIF) projects. The panel presented an in-depth analysis of the ways in which student-teacher linkages can be compromised and detected. The presentation also identified factors that impact the quality of student-teacher data linkages in a large urban district as well as the methods used to identify and fix those problems as close to the source of the problem as possible.

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Getting Student-Teachers Linkages Right! (260 KB)

Sessions in Data Quality track:

II-H, III-D, V-D, VII-H, IX-D, X-D, XI-H

The first hour of a two-hour session provided an overview to the 2007-08 and 2008-09 EDFacts Submission System. EDFacts and Partner Support Center staff discussed issues that have arisen in reporting and how they are being resolved, as well as changes state EDFacts Coordinators can expect to see in 2008-09. The session was intended as a comprehensive briefing for state EDFacts Coordinators. See also Part II.

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Operationalizing EDFacts
- A Session for SEA EDFacts Coordinators and Staff - (657 KB)

Sessions in EDFacts track:

II-E, III-E, IV-E, V-E, VI-E, VII-E, VIII-E, IX-E, X-E, XI-E

In this session the Regional Education Laboratory-Southwest, managed by Edvance Research in San Antonio, Texas, discussed the challenges and opportunities for state education agencies (SEAs) and researchers to work together to build stronger evidence of effective interventions and programs.

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Cracking the Glass Walls: Using Education Data for Research (1.5 MB)

Sessions in Data Use/Data Standards track:

I-C, I-D, I-E, II-A, II-C, III-C, IV-C, IV-H, V-C, V-H, VI-C, VII-A, VII-C, VIII-C, VIII-H, IX-A, IX-C, IX-F, IX-H, X-A, X-C, X-F, XI-A, XI-D, XII-C, XII-D

In order to facilitate and promote education research in Kansas, the Kansas Education Data Users Consortium (KEDUC) has been formed through partnership with the Kansas State Department of Education, Kansas Board of Regents, and our two major research universities (University of Kansas and Kansas State University). This presentation provided information regarding how KEDUC is organized, how work is accomplished through committees, and what are the specific objectives of the Consortium and of each of its committees. In order to develop a state Research Agenda, KEDUC has also developed and administered a Needs Assessment Survey to education stakeholder groups throughout the state. The survey and results were shared, along with plans for the Research Agenda. Lessons learned along the way and plans for the future were also included in the presentation.

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Moving Education Forward in Kansas Through Partnerships (1.8 MB)

Sessions in Longitudinal Data Systems (LDS) track:

I-G, II-G, III-G, IV-G, V-G, VI-G, VII-G, VIII-G, IX-G, X-G, XI-G, XII-G

The Center for Technology in Education at Johns Hopkins University (CTE) in partnership with the Maryland State Department of Education (MSDE) has developed a user interface that provides special education leaders with information to assist with progress monitoring. The MD IDEA Scorecard site provides three ways of viewing student performance data: MD IDEA Reports, MD IDEA Scorecard and MD Online IEP Reports. The available reports serve as monitoring tools for the State Performance Plan, tools to monitor effects of interventions and review individual student profiles. This session was a demonstration of the reporting functions of the applications and described their use in supporting MSDE and local school systems.

Sessions in Data Use/Data Standards track:

I-C, I-D, I-E, II-A, II-C, III-C, IV-C, IV-H, V-C, V-H, VI-C, VII-A, VII-C, VIII-C, VIII-H, IX-A, IX-C, IX-F, IX-H, X-A, X-C, X-F, XI-A, XI-D, XII-C, XII-D

English language learners (ELLs) are often viewed as struggling learners who negatively impact overall performance data for schools and districts. However, many ELLs in Washington State demonstrate enormous growth from year to year and ultimately outperform the state average on the reading and writing Washington Assessment of Student Learning (WASL), and, in some cases, the math WASL. What types of data demonstrate the growth and progress of ELLs, and how can districts use this data to evaluate the success of their programs for ELLs? Examples of this data and multiple data success stories were provided as part of this presentation.

Sessions in Washington State track:

I-I, II-I, III-A, III-I, IV-I, V-I, VI-I, VII-I, VIII-F, VIII-I, IX-I, X-I, XI-I, XII-I