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Lori McReynolds, Kansas Tiffany Smith, Kansas Phil Koshkin, Maryland Brian Morrison, Maryland

Incorporating EC Data i nto Your State’s L ongitudinal D ata System: Why Does it Matter to Part C and 619 ?. Lori McReynolds, Kansas Tiffany Smith, Kansas Phil Koshkin, Maryland Brian Morrison, Maryland Amy Nicholas, DaSy Missy Cochenour, DaSy/SLDS State Support Team.

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Lori McReynolds, Kansas Tiffany Smith, Kansas Phil Koshkin, Maryland Brian Morrison, Maryland

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  1. Incorporating EC Data into Your State’s Longitudinal Data System: Why Does it Matter to Part C and 619? Lori McReynolds, Kansas Tiffany Smith, Kansas Phil Koshkin, Maryland Brian Morrison, Maryland Amy Nicholas, DaSy Missy Cochenour, DaSy/SLDS State Support Team

  2. Session Objectives • The objectives for this session are to: • Provide basic information about the differences between an Early Childhood Integrated Data System (ECIDS) and a Statewide Longitudinal Data System (SLDS); • Share the perspectives and experiences of panelists as they discuss how their states are working to build ECIDs and incorporate EC data into their SLDSs; • Review state and national examples, and present the unique challenges and benefits to building ECIDSs, particularly as theyrelate to the inclusion of Part C and Part B 619 data; and • Discuss why having an integrated longitudinal data system matters to Part C and Part B 619.

  3. National Overview Federal Motivators • President's early childhood education budget • NCES- SLDS Program • RTT-Early Learning Challenge • OSEP/IDEA Reporting Requirements • HHS Federal Reporting (Head Start, Home Visiting, QPR) • Early Childhood Advisory Councils

  4. National Context Where are states trying to go? • They are all in very different places: • Pre- Planning (thinking): Which states are thinking of expanding SLDS to include early childhood? Which states are planning to coordinate their SLDS with their ECIDS? • Three stages: • Planning (actually developing a work plan) • Implementing (implementing the work plan and beginning to build) • Leading (providing lessons learned from the work) • Phased development (a certain number of programs included in each phase)

  5. Lessons Learned Governance matters! • Data contributors need to be included early on in the conversation • May make things move more slowly in the beginning, but will be beneficial in long term Understand the unique needs of early childhood Leverage lessons from other sectors Data use improves data quality; data use depends on access The devil is in the details (e.g. Unique ID - we may all agree on what this is until we have to develop the process for making come to life)

  6. How do I know if there is a SLDS and/or ECIDS initiative taking place in my state? Which states have a federal SLDS grant? Which states are working on an ECIDS?

  7. SLDS Grant Program Evolution 2012 Competition 2006 & 2007 Competitions 2009 Competition 2009 ARRA Competition K12 + ONE of the following: EC, Postsec, Workforce, OR Student-Teacher link K12 + ALL of the following: EC, Postsec, Workforce, AND Student-Teacher link ONE of the following: K12, EC, OR Postsec/ Workforce K12 24 $4.1M 20 $12.5M 14 &13 $3.7M& 4.8M 27 $5.6M # of grants: Avg. award:

  8. FY06 Awards

  9. FY06 FY07 Awards

  10. FY06 FY07 FY09 Awards

  11. FY06 FY07 FY09 FY09 ARRA Awards

  12. FY06 FY07 FY09 FY09 ARRA FY12 Awards

  13. RTT-ELC Grant Context One subsection of the grant program relates to the development of an ECIDS (Subsection E2) 10 out of 14 grantees have an ECIDS included in their scope of work Many states are building upon the work supported by SLDS grants

  14. RTT-ELC Grant: ECIDS Projects FY06 FY07 FY09 FY09 ARRA FY12 Awards

  15. So what does this mean for Part C and 619? • Many states are moving forward with creating and linking their ECIDS to their K12 and beyond SLDS. • Federal support can be leveraged to establish the state governance and infrastructure needed to involve Part C and 619 in the work and sustain this involvement over time. • The DaSy Center • SLDS Early Childhood State Support Team

  16. How are Part C and 619 being involved in ECIDS initiatives? • Kansas • School Readiness Framework • Build from lessons learned from Part C and 619 • Unique Identifier (KIDS ID) for Part C & 616 • Maryland • The Maryland State Department of Education’s Division of Early Childhood Development is leading the ECIDS initiative • Part C and 619 have worked with the initiatives leaders to identify data elements to be integrated

  17. What benefits have states identified with including Part C and 619 data in their ECIDS? • Kansas • A shared child outcomes data system for Part C & 619 APR data • Being included in the state conversation around EC Initiatives • Support of our IT Director • EC Leadership Team developed • Maryland • More comprehensive data for school readiness policy planning, resource allocation, and kindergarten assessment data analysis

  18. What unique challenges have states experienced when integrating Part C and 619 data into their ECIDS? • Kansas • Determining accessible and additional data needed • Aligning our data standards through CEDS • Data system only meets Federal requirements • Only child-specific data obtained through 619 • Maryland • Increased privacy concerns • Differences in data collection and reporting • How can we make the ECIDS useful to Part C/619 given they have a robust longitudinal data system of their own?

  19. July 2013

  20. Sample Maryland Analysis #1 • How does participation in Part C enhance children’s later performance on the Kindergarten Work Sampling System (WSS-K; i.e. state kindergarten readiness assessment)? • For every month earlier a child starts receiving services, he/she is expected to score .017 SD increase on the WSS-K. • For children receiving Part C services, WSS-K was higher for students not economically disadvantaged, higher for girls, and for White students. Source: Carran, D., Nunn, J., Hooks, S., & Dammann, K. (2013, February). Uses of a Statewide Longitudinal Data System to evaluate and inform programs, policies, and resource allocations. Presented at26th Annual Management Information Systems Conference, Washington, DC.

  21. Sample Maryland Analysis #2 • For children who received Part C services, where are they at Grade 3? (N = 2482) • 58% missing data, not matched Part C to Grade 3 • 65.6%, n = 1,628 enrolled as General Education student at Grade 3 • 34.4%, n = 854 enrolled as Special Educationstudent at Grade 3 Source: Carran, D., Nunn, J., Hooks, S., & Dammann, K. (2013, February). Uses of a Statewide Longitudinal Data System to evaluate and inform programs, policies, and resource allocations. Presented at26th Annual Management Information Systems Conference, Washington, DC.

  22. Sample Maryland Analysis #3 • For children who received Part C services, how do they compare to their General Education and Special Education peers on Grade 3 State Academic Assessments? Source: Carran, D., Nunn, J., Hooks, S., & Dammann, K. (2013, February). Uses of a Statewide Longitudinal Data System to evaluate and inform programs, policies, and resource allocations. Presented at26th Annual Management Information Systems Conference, Washington, DC.

  23. Maryland Grade 3 Students:Average State Assessment Scores at Grade 3 Scores by Previous Part C and Special Education Status • *Special Education = eligibility of Speech/Language, Specific Learning Disability, Emotional Disturbance or Other Health Impairment Source: Carran, D., Nunn, J., Hooks, S., & Dammann, K. (2013, February). Uses of a Statewide Longitudinal Data System to evaluate and inform programs, policies, and resource allocations. Presented at26th Annual Management Information Systems Conference, Washington, DC.

  24. State Level Analyses Conclusions: Children in Grade 3 • Children in General Education • When controlling for race, gender, and FaRMs, Reading and Math scores are higher for: • Students not receiving FaRMs; • Females; and • White students. • Students with a history of Part C scored slightly lower on average (Reading: 3.1 M diff; Math: 1.3 M diff) • Children in Special Education • When controlling for race, gender, and FaRMs, Reading and Math scores are higher for: • Students not receiving FaRMs; • Females; and • White students • Students with a history of Part C scored lower on average (Reading: 22.3 M diff; Math: 16.2 M diff)

  25. What hopes and dreams dostates have for their integrated systems? • Kansas • What we hope to gain from our involvement • Vision Statement: Meaningful, accessible information for children, families, educational environments and communities to attain school readiness and success for all Kansas children. • Questions we hope to be able to answer that we aren’t able to answer now • Have identified eight priority policy questions

  26. What hopes and dreams do states have for their integrated systems? • Maryland • Implementation of a statewide Birth through 21 model for data-driven decision-making by state and local district special education/early intervention teams • Improve timeliness of data exchange between special education data warehouse and general education systems • Daily refreshing of data for purposefully-selected research-based data elements associated with school performance • Allow for near real-time analyses

  27. Audience Poll Activity Source: Google Image

  28. Wrap-Up: Comments and/or Questions Source: Google Image

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