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Advancing Data Culture One Step at a Time

Advancing Data Culture One Step at a Time. Haidee Bernstein, SRI Lisa Backer, MN Department of Education Mary Anketell, PA Early Intervention & Technical Assistance Program. STATS DC July 2019. Session Objectives. Define and provide context for data culture

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Advancing Data Culture One Step at a Time

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  1. Advancing Data Culture One Step at a Time Haidee Bernstein, SRI Lisa Backer, MN Department of Education Mary Anketell, PA Early Intervention & Technical Assistance Program STATS DC July 2019

  2. Session Objectives • Define and provide context for data culture • Tour of the DaSy Data Culture Toolkit • Learn what is happening in MN and PA • Share your thoughts

  3. What is data culture? Focuses on Continuous Improvement Puts the believe in using data into practice Data Culture

  4. “Culture does not change because we desire to change it. Culture changes when the organization is transformed; the culture reflects the realities of people working together every day.” – Frances Hesselbein

  5. What is your data culture environment? This Photo by Unknown Author is licensed under CC BY-NC-ND This Photo by Unknown Author is licensed under CC BY-SA

  6. What ingredients do you need? https://www.wholewhale.com/tips/data-culture-building/

  7. Data Culture Toolkit https://dasycenter.org/data-culture-toolkit/

  8. Pennsylvania’s Early Intervention Data Literacy Initiative Building Better Use of Early Intervention Data

  9. Data Literacy Initiative • Goal – Provide Early Intervention Leaders with the skills to effectively use their data to make program improvements.

  10. Data Literacy Academy • Two-day leadership event • All participants to attend breakouts • Building a Local Data Team • Answering Critical Questions Using Data • Strategies for Monitoring Data Quality • Data Visualization Strategies

  11. Supports before the Academy • Early Intervention Reports 101 Webinar • How to “Read” the Monthly/Yearly Reports Webinar

  12. Supports at the Academy • Early Bird Session on Tips and Tricks for Using Excel • PELICAN Information Desk • Access to Technology Resources

  13. Building a Culture of Data Use • Supports after the Academy • Model data use • Continue professional development • Local communities of practice related to data use

  14. What changes were sustained What challenges remain Local implementation of data literacy teams Strategies for supporting new leaders in data use • State-level modeling of data use • Increased use of data in local determinations and monitoring • Continued professional development on data literacy

  15. Supporting Meaningful Data Use-Internal and External Lisa Backer| Education Supervisor-IDEA Part C and B/619 DC Stats: July 2019

  16. External: Local Program Assessment

  17. INSPIRE education.state.mn.us

  18. ACTION education.state.mn.us

  19. Promoting data use at all levels: Investment in Tableau Leading for educational excellence and equity, every day for every one.|education.mn.gov

  20. MN Dept. of Education Data Infrastructure Student Information System- • Child demographics • Federal Setting and Disability Category* • Dosage—planned and received Personnel Information System Minnesota Common Course Catalog • Attributes of early education (curriculum, assessment, site-based initiatives) • Level of fidelity attained by teaching team (beginning, expanding or maintaining) • Links instructional staff to enrolled children

  21. MnCoE Data Infrastructure Fidelity of Implementation • State Benchmarks of Quality • Local Benchmarks of Quality* Quality and effectiveness of training • End-of-event survey • Follow-up survey Coaching log* • Coaching model • Frequency and focus PDF Time and Effort Log* Fidelity of Practice* • Pyramid: TPOT & TPITOS • FGRBI: SS-OO-PP-RR Key Indicator Observation • CEM: CEM Checklist Child Event Tools • Behavior Incident Report--Pyramid • Scale for Teacher’s Assessment of Routines Engagement (STARE)--CEM Fiscal Data Data from tools marked with * are being merged into EC Real-time Data Warehouse

  22. Data Integration: Phase I Connect MnCoE data to MnCoE data • How much coaching is needed to support a teacher to reach fidelity? • Are 1:1 coaching and group coaching equally effective? • Does fidelity of implementation as measured by the Benchmarks of Quality increase fidelity of practice? • Does PDF effort predict fidelity of implementation?

  23. Data Integration: Phase I (cont.) Connect MDE data to MDE data • Does intensity of intervention services or time in a regular early childhood setting correlate with higher child and family outcomes? • Does intervention environment or preschool instructional setting influence outcomes? • To what extent is the use of a particular curriculum or assessment tool correlated with better child outcomes?

  24. Data Integration Phase II: Connecting MnCoE and MDE Data Do children benefit more when teachers/providers demonstrate fidelity of practice? • OSEP Child Outcomes? • Mastery of Minnesota Early Learning Standards (ECIPS)? • Reduction in referrals to special education in kindergarten? • Reading well by 3rd grade? • Higher graduation rates? • Post school outcomes?

  25. PLEASE COMPLETE THE EVALUATION!! • 4 ways: • Paper forms (submission boxes near registration table) • Go to https://www.surveymonkey.com/r/2019STATS-DC • Conference app under “Evaluation Forms” • Scan the QR code: Session Number: [Enter Your Session Number, i.e., 2-A]

  26. Learn more and share your thoughts • Visit the DaSy website at:http://dasycenter.org/ • Like us on Facebook: https://www.facebook.com/dasycenter • Follow us on Twitter:@DaSyCenter

  27. Thank You The contents of this presentation were developed under a grant from the U.S. Department of Education, #H373Z120002. However, those contents do not necessarily represent the policy of the U.S. Department of Education, and you should not assume endorsement by the Federal Government. Project Officers, Meredith Miceli and Richelle Davis.

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