A panel of recipients of the Statewide Longitudinal Data Systems grants discussed their approaches to including formative assessments in their data systems, improving data quality, and providing training to users. The panel shared the lessons learned and plans for the future.

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P-12 Data Systems: New Developments and Lessons Learned (1.72 MB)

Sessions in LDS track:

I-A, II-A, III-A, IV-A, V-A, VI-A, VII-A, VIII-A, IX-A, X-A, XI-A, and XI-D

When the Maryland Department of Education turned to Johns Hopkins University (JHU) to assist in planning and overseeing its longitudinal data management system efforts, JHU selected ESP Solutions Group's DataSpec tool to manage the metadata and build a data dictionary. This session provided a hands-on exploration of the resulting on-line metadata management site.

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Maryland-Johns Hopkins University Metadata Partnership (602 KB)

Sessions in Statewide LDS track:

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

Large information systems, by definition, collect data from many different sources and provide those data to many different individuals for many different uses. With so many diverse data perspectives, the information system management team must devote considerable time and energy to establishing and maintaining communication and agreement on valid data definitions and use. This session described the EDFacts team's processes to establish data stewards and agency-wide collaboration.

Sessions in EDEN/EDFacts track:

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

American high schools have been characterized as dropout factories. It is common knowledge that dropouts are more likely to have a lower quality of life. In situations where students begin to deviate toward dropping out, schools must intervene in productive ways that will redirect these students toward success. One safety net is an information system designed to identify potential dropouts so that intervention strategies can be put into action to make this option less desirable for the student. This paper discussed the efforts associated with the implementation of a state-wide Dropout Early Warning System.

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Implementing a Statewide Dropout Early Warning System (984 KB)

The Education Data Exchange Network (EDEN) system has incorporated many of the Common Core of Data's (CCD) edit rules. This session described some of the additional checks the U.S. Census Bureau and NCES carry out on the CCD data. Participants were encouraged to ask questions about data anomalies they have encountered in reporting CCD data.

Sessions in Federal track:

I-F, II-F, III-F, IV-D, IV-F, V-D, V-E, V-F, VI-D, VI-F, VII-D, VIII-E, X-E, and XI-E

Presenters observed the livelihoods of former public school teachers after they leave teaching to better understand the teaching profession. They drew evidence from a nationally-representative data set of college graduates in 1993 a decade after they graduated (Baccalaureate and Beyond, 93/03). Unlike earlier work (Henke, 2007), presenters examined only former public school teachers who are employed full time in 2003, examining their description of their actual work, rather than using broad occupational categories. Additionally, presenters observed how various career paths and personal characteristics impact the wages of former teachers. A key finding is that those few who leave the public school teaching profession do so because of a lack of career opportunities within public school teaching. Generally, former public school teachers use their current skill sets in their new livelihoods, rather than obtaining extensive retraining for employment in vastly different occupations.

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What Does the Livelihood of Former Public School Teachers Tell Us About the Teaching Profession? (92 KB)

Many questions have come about as SEAs and LEAs work to fulfill the EDFacts reporting requirements. Are we capturing the right data elements at the LEA level? Will we be able to automate the collections top to bottom? What are the impacts at the various levels? The SIF Association as well as the EDFacts team has been addressing these questions as we work on mapping the file specifications to SIF and understand the gaps that exist and the ability to automate the collections. Presenters explored the current work being done to answer the questions in a comprehensive and meaningful way.

Sessions in SIF track:

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

The Ohio credentialing system for educators known as Connected Ohio Records for Educators, or CORE, was re-architected to bring it into the 21st century. What was once a flat file system was converted into a Oracle relational database. This has brought significant structure, validity and access upgrades to the data contained in the system. The presentation focused on those changes as well as the various tolls and reporting features of the new CORE.

The Suffolk Regional Information Center (RIC) offers several web-based tools that help districts analyze the K-12 student achievement information contained in the data warehouse. These tools allow district administrators and teachers to generate timely and relevant disaggregated reports of student performance on Reading First early skills assessments, elementary/middle level state assessments, and secondary Regents exams. There are over 300,000 active student records in our data warehouse and millions of test records.