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Pathways between k-12, higher education and employment: patterns from ohio administrative data

Pathways between k-12, higher education and employment: patterns from ohio administrative data. Dr. Josh Hawley and Dr. Lisa Neilson The Ohio State University. 26 th Annual MIS Conference| Washington, DC | 2.13.2013. OERC Mission Statement.

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Pathways between k-12, higher education and employment: patterns from ohio administrative data

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  1. Pathways between k-12, higher education and employment: patterns from ohio administrative data Dr. Josh Hawley and Dr. Lisa NeilsonThe Ohio State University 26th Annual MIS Conference| Washington, DC | 2.13.2013

  2. OERC Mission Statement The Ohio Education Research Center (OERC), is a network of Ohio-based researchers and research institutions, that develops and implements a statewide, preschool-through-workforce research agenda to address critical issues of education practice and policy.

  3. Primary Objectives • Provide timely and high quality evaluation and research products for state, federal and private agencies as well as other policy informing organizations; • Maintain a research database that includes restricted administrative records in a secure environment, while also increasing researcher access to data; • Serve as a bridge to education practitioners, researchers and policymakers translating the needs of practitioners into the research agenda and research into actionable practice improving policy at all levels of education; and • Bring together diverse resources on education throughout the state to improve access to high quality knowledge.

  4. Research agenda • State Success Factors • How do state level actions (e.g. policies, programs, laws) facilitate success in Ohio schools? • Ex: How have state efforts to create and support transformation teams lead to better educational outcomes? • Standards and Assessments • How are standards and assessments contributing to the success of Ohio schools? • Ex: Are teachers who are rated high on Student Growth Measures also rated high on Teacher Standards on Performance?

  5. Research agenda • Improving with Data • How can educators and policymakers effectively use data to improve practice and inform strategic decision-making? • Ex: to what extent are LEAsusing data to improve student graduation from high school and completion of college? • Teachers and Leaders • What policies, programs, practices, and resources are necessary to ensure that every Ohio student has effective teachers and education leaders? • Ex: How effective are teacher residency programs at preparing effective teachers?

  6. Research agenda • Improvement and Innovation • What strategies and models are most successful in improving schools and decreasing achievement gaps in Ohio? • Ex: To what extent have innovative models such as New Tech or AVID been effective at increasing student achievement overall and reducing the gaps between disadvantaged and advantaged student populations? • STEM Education Initiatives • What are the impacts of STEM education on student performance, post-secondary education decisions and the workforce? • Ex: What impacts do STEM schools have on college entrance and completion? How have disadvantaged and advantaged students been impacted differently by STEM school participation?

  7. Research agenda • Early Childhood Education • What are the leverage points in early childhood that will positively impact school readiness? • Ex: To what extent have innovative models such as New Tech or AVID been effective at increasing student achievement overall and reducing the gaps between disadvantaged and advantaged student populations? • Future-Ready Students • What effect does infrastructure and programming have on the state’s ability to reach college and workforce goals? • Ex: Do dual credit (or advanced placement) programs increase student retention in and completion of college degrees? How do high school programs and policies (e.g., counseling or testing programs) decrease the need for remediation in college?

  8. State data systems: guiding principles • Comprehensive data (e.g., encompasses major state data sources) • System linkages (e.g., early childhood data to K-12, teachers to students) • Testing and outcome data (e.g., analysis of student and teacher level effectiveness) • Access to consistent and updated documentation

  9. Data application • What is the economic payoff for educating college students? • For the state • For the student • Matched student records to earnings • Linked the HEI student data with their Ohio earnings 1 year after graduation and 5 years later • 1) Identified graduates • 2) Extracted student data • 3) Extracted wage data • 4) Aligned timing of earnings to term of graduation

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  11. Next steps • Outcomes of higher education: • Earnings by degree and subject  • Match with chosen field • - Match wage data with industry codes • Compare to high school graduates

  12. Thank you . connect@oerc.osu.edu | www.oerc.osu.edu

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