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Nancy J. Smith, Ph.D. Longitudinal Data Systems Initiatives NCES

Connecting Policymakers, Researchers, and Statewide Longitudinal Data: How to Make the Most of These Robust Data Systems. Nancy J. Smith, Ph.D. Longitudinal Data Systems Initiatives NCES. Goals of the SLDS Grant Program.

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Nancy J. Smith, Ph.D. Longitudinal Data Systems Initiatives NCES

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  1. Connecting Policymakers, Researchers, and Statewide Longitudinal Data: How to Make the Most of These Robust Data Systems Nancy J. Smith, Ph.D. Longitudinal Data Systems Initiatives NCES

  2. Goals of the SLDS Grant Program Enable grantees to design, develop, and implement SLDSs to efficiently and accurately manage, analyze, disaggregate, report, and use individual student data. The long term goals of this program are to: 1) 2) 3) 4) 5) identify successful instructional programs and facilitate use of research to improve instruction determine whether graduates have knowledge and skills to succeed in postsecondary education and the workforce simplify the processes used by state education agencies to make educational data transparent through local, state, and federal reporting support informed decisionmaking at all levels of the education system permit the generation and use of accurate and timely data http://nces.ed.gov/programs/SLDS

  3. Framework for Connecting Researchers and State Longitudinal Data Systems • Contracted with Education Statistics Services Institute (ESSI) • Subcontract with National Institute of Statistical Services (NISS) • Working Group members • Alan Karr, NISS, Chair • Chrys Dougherty, National Center for Educational Achievement • Deborah Jonas, Virginia Department of Education • Ellen Mandinach, CNA NISS The Statistics Community Serving the Nation

  4. Framework for Connecting Researchers and State Longitudinal Data Systems • Goals: • Articulate a framework to encourage policy-relevant research that employs SLDSs; and • Formulate actionable recommendations, both immediate and ongoing, to implement that framework, including incentives for researchers and means to overcome barriers. • Input from 4 communities: • SLDS “owners”: SEAs; • Policy makers at the state and national levels; • Academic and other researchers who are potential “consumers” of SLDS data ; • Experts in data confidentiality and statistical analysis of distributed data. NISS The Statistics Community Serving the Nation

  5. Connecting Researchers and SLDSs The most recent American Recovery for Reinvestment Act (ARRA) request for applications for SLDS development encouraged applicants to establish a policy for research access: “States are encouraged to develop partnerships with external research organizations and must include in their applications and plans strategies for providing researchers access to State data for evaluations of policies and programs within the State, with appropriate safeguards to protect student confidentiality.”

  6. Building the Foundation • Working models for research access to student-level data exist (TX, FL, NC, VA, KS) • Educational improvements … are more likely to be sustained when they are guided by sound and widely understood research based on high-quality data. • There exists a growing cadre of researchers with both the right motivation and the right skills to carry out high-impact research.

  7. Real and Perceived Barriers • Lack of resources to support access to the data • Misconceptions both internally and externally related to FERPA • External researchers are not interested in applied or policy-relevant research • External researchers do not treat confidentiality seriously • SEAs are not receptive to use of SLDS data for theoretical research • Practice is not informed by research • Institutional Review Board (IRB) protocol review is all that is required to meet federal and state data security and privacy requirements

  8. Road Map to Change Funding and Business Models • Start-up funds and sustainable funding sources • Staffing models (NAEP State Coordinator, REL, shared staff) • Research Data Centers • Governance Structure Need some good use cases to highlight • Research to demonstrate value of SLDS • Research to support access to SLDS Bottom line • Communication with SEAs • Communication with Researchers • Communication with Policy Makers

  9. CDS is Building a… Voluntary Common Vocabulary

  10. Who Needs ‘Common’? State and local K-12 education agencies and higher education organizations are building or expanding their data systems to meet the needs of: • Students as they transfer across districts and move from K-12 to higher education; • Policymakers who are looking for comparable indicators of student achievement; and • Educators who use transcript information and academic history to individualize instruction.

  11. What is CDS Doing? CDS Objective: • Identify a minimal set of key data elements • Come to agreement on definitions, business rules, and technical specifications • Work with State and local education agencies and higher education organizations to document agreed upon common data standards Focus on: • Data definitions and code sets – Concerned with the meanings and contents (e.g., values) of data elements. • Business rules – Explicit guidelines for using or modifying a particular data element. • Technical specifications – Used by software and systems developers to facilitate interoperability between applications or to guide data reporting.

  12. Why Do We Need ‘em? Because lack of standardization… …across SEAs and LEAs hampers our ability to share data and make valid comparisons of student performance. …across K-12 and postsecondary sectors makes it cumbersome to exchange student-level data with state public higher education entities.

  13. What are the Benefits? So, use of common data standards can: Increase comparability of data across state lines, allowing us to draw valid comparisons Increase interoperability and portability of data within K-12, across SEAs, and with the postsecondary sector Provide clarity for districts on what to collect

  14. CDS is NOT… Required: Adoption of any or all of the CDS standards is entirely voluntary. A data collection: CDS does not collect data. A Federal unit record system: CDS is a model for data standardization to enable sharing between state systems. Solely a USED undertaking: CDS is a collaborative effort including SEAs, LEAs, state higher education organizations, and national organizations.

  15. CDS is … A national, collaborative effort: CDS includes participants from SEAs, LEAs, higher education organizations, key non-profit organizations, and USED. Developing voluntary standards for key elements: CDS is targeting a core subset of K-12 and K12-to-postsecondary education transition elements that may be voluntarily adopted by education stakeholders. Building off of existing Standards sources:  CDS elements and standards are almost entirely drawn or adapted from existing national standards sources. Intended to improve the share-ability of data: Use of common data standards increases the interoperability, portability, and comparability of education data.

  16. Where are they? www.commondatastandards.org Version 1.0 Release Date: Sept 2010

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