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Surfing the Data Standards: Colorado’s Path

Surfing the Data Standards: Colorado’s Path . 2012 MIS Conference – San Diego Daniel Domagala, Colorado Department of Education David Butter, Deloitte Consulting LLP Zeynep Young, Double Line Partners . The SEA Data Challenge . The IT Reality. Many source systems

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Surfing the Data Standards: Colorado’s Path

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  1. Surfing the Data Standards: Colorado’s Path 2012 MIS Conference – San Diego Daniel Domagala, Colorado Department of Education David Butter, Deloitte Consulting LLP Zeynep Young, Double Line Partners

  2. The SEA Data Challenge

  3. The IT Reality • Many source systems • Escalating technology demands • Constrained resources • Dependent on vendor cooperation Education data management isdecentralized and complex

  4. Colorado Situation • CDE collects a wide variety of information from 178 LEAs to support different requirements: • Monitor compliance with federal and State law, regulations and standards. • Preparation of federal reporting requirements. • Respond to State legislative and board of education data requests. • Produce annual statewide summary publications. • Determine if classes are receiving instruction from Highly Qualified Teachers. • 22 different data collections at different points in the school year • ASCII flat-file, fixed field formats are used for each collection

  5. Complex submission and resubmission process for each collection Changes

  6. Web Data Collection System Objectives • Reduce the number of re‐submissions by an LEA for a given collection by 50% • Reduce the overall number of collections by 20% • Reduce data redundancy so that the total number of data elements collected is reduced by 20% • Provide an extensible system to support future data collection technology • Provide a technology that supports rapid data exchange and accommodates new data elements

  7. Surfing the data standards Increasing Levels of Operational Specificity Implementing Entity NCES CEDS Ed-Fi “Data Handbook” “Data Definitions” “Data Model” “Implementation Guide” Provides users with a list of data elements to help ensure consistency Provides users a list of data elements with definitions and code sets, with a focus on the meaning of data stored in a SIS Provides users a model for exchanging education data Provides users documentation on how to use, adapt, and extend the model

  8. Surfing the data standards Increasing Levels of Operational Specificity Implementing Entity NCES CEDS Ed-Fi “Data Handbook” “Data Definitions” “Data Model” “Implementation Guide”

  9. Surfing the data standards Increasing Levels of Operational Specificity Implementing Entity NCES CEDS Ed-Fi “Data Handbook” “Data Definitions” “Data Model” “Implementation Guide” “Data Handbook” PLUS

  10. Surfing the data standards Increasing Levels of Operational Specificity Implementing Entity NCES CEDS Ed-Fi “Data Handbook” “Data Definitions” “Data Model” “Implementation Guide” “Data Handbook” PLUS “Data Definitions” PLUS

  11. Surfing the data standards Increasing Levels of Operational Specificity Implementing Entity NCES CEDS Ed-Fi “Data Handbook” “Data Definitions” “Data Model” “Implementation Guide” “Data Handbook” PLUS “Data Definitions” PLUS “Data Model” PLUS

  12. Ed-Fi streamlines the data collections By continuously collecting fine-grained education data throughout the year, satisfying the various reporting requirements are isolated for maximum efficiency. Student Information System (SIS) District Source Systems & Raw Data Web Data Collection System Operational Data System Reporting Federal reporting State reporting Other District Source Data Legislative requests Operational Data System (ODS) Board requests Annual summaries Ed-Fi XML Interchanges Ed-Fi Database Schema Funding, Budgets, and Actuals • Single, adaptable infrastructure • Most new reporting changes can be handled without impact to the LEAs This process is completed for each LEA

  13. Web Data Collection System

  14. We believe Ed-Fi is a positive and transformational force in using education data…. and our actions demonstrate our beliefs

  15. For Colorado - Acceleration

  16. For Colorado and Beyonda portfolio of low cost and rapidly deployed Ed-Fi APPs that improve student outcomes in real time. Program & Financial Effectiveness Educator Effectiveness High School Feedback Reporting Eden & EDFactsReports Automation Early Warning Systems

  17. Conclusions • Ed-Fi brings the years of education standards activities to a point where CDE can implement and tangibly benefit from it. • Fine-grained SEA data collection from LEAs should reduce overall data collection costs. • Supporting data collection infrastructure needs to flexible for future extensions.

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