Data Analysis and Research 2012 SLDS Grant

1. Data Analysis and Research2012 SLDS Grant Marilyn Peterson and Russ Masco Nebraska Department of Education Data Conference April 29-30, 2013 NE Data Analysis and Research

2. Goals of the 2012 Grant • Provide a dashboard for districts • Provide professional development in data use and analysis to every district • Establish a research and evaluation section within the Nebraska Department of Education • Activities to support NSSRS • Documentation for the system – data governance, data dictionary, metadata • eScholar Interstate Locator NE Data Analysis and Research

3. Dashboard Adata analysis tool for districts that uses multiple local and state data sources to produce reports for local decision makers. Data Analysis and Reporting Tool (DART) • Adopting the Ed-Fi Alliance dashboard tools • Using Nebraska data to answer Nebraska’s questions • Optional for districts NE Data Analysis and Research

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6. Ed-Fi Alliance Information • http://www.ed-fi.org/ Other Sites: • http://www.doe.k12.de.us/EdInsight/files/Elem_Classroom_Set.pdf NE Data Analysis and Research

7. Data Dashboards • Compile key pieces of information in a simple and easy to interpret display • Present data so one can quickly and visually see status or progress, etc. • Combine data from various streams, including state and local, to present a clear and comprehensive picture NE Data Analysis and Research

8. Nebraska’s dashboard • Store the local and state data in a holding box at the NDE that is separated from all other NDE data • Pull data from district systems to load and the holding box daily • Provide secure access at teacher (classroom), building, and district levels NE Data Analysis and Research

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10. NSSRS and the Dashboard • NSSRS is a warehouse • Data entered only at specified times, summary or end-of-year data • All NSSRS collections continue • Dashboard data must be real-time data • More and different data needed • Dashboard will “pull” the data from the district systems • Only the district submitting the data can see their data NE Data Analysis and Research

11. Design Team • Districts or ESUs wanting to provide input into the data selected for the dashboard must • Commit to holding a meeting of classroom teachers and administrators before the end of this school year • NDE will provide agenda, instructions and process • Brainstorm ideas and make recommendations • Design Team leader will take ideas, complete an inventory on a file we provide and submit it • NDE will analyze all district input to identify the highest priorities NE Data Analysis and Research

12. Pilot Districts • Will be asking for districts to volunteer to pilot the dashboard • Must contribute staff time to help adopt the Ed-Fi dashboard (Assembly Team) • SLDS grant will pay for staff time • Estimated time – still uncertain • Starting this summer • Work on standardizing data to be in dashboard • Use their data to develop prototype NE Data Analysis and Research

13. Proposed Timelines • Development • Design Team • Input submitted to NDE by end of June • Pilot Districts • Selected by this summer, begin work in the Fall • Pilot Prototype • By end of 2013-14 school year • Available then for any district that wants to use it NE Data Analysis and Research

14. Challenges -- • Data from districts is pulled daily • Districts may not update their data daily • Standards are needed for data stored by the district • Other data not in NSSRS may not have standard definitions • Districts have different information systems • At least a dozen different systems for student data • Dashboards use data that may not be electronically stored • Classroom teacher and student pictures for example NE Data Analysis and Research

15. Advantages -- • Problems with data are found early when data is updated to dashboards daily • May be (big maybe) someday NDE will be able to pull NSSRS data that it needs from the dashboard warehouse and then districts would not need to submit NE Data Analysis and Research

16. Other SLDS Activities • Research and Evaluation Team • Establishing a team within NDE • Support and conduct research and evaluation • Documentation • Data Governance Plan, Data Dictionary aligned with Common Education Data Standards (CEDS), Metadata • Interstate Locator • An eScholar module that finds students who move to other states in the project (Iowa, Kansas, Missouri) NE Data Analysis and Research

17. Due Dates and Data Changes • NEW processes • Every Due Date will be followed by an Auditing Window • A period of time when data can be changed before it is considered final • Announced on the Master Calendar and other calendars • Requests • When Due Dates are missed and Data Changes are needed after it is considered final • Requests found in the Consolidated Data Collections

18. SLDS Grant Goal 2 Also known as “Data Cadre” • Statewide model of professional development centered around the use of data for continuous school improvement • Collaborative model between NDE, ESUCC, and ESUs • Focus on the analysis of data to inform professional development, instructional practices, evaluation processes and school improvement

19. Centered Arounda Framework that assists in • Understanding how to interpret a variety of data • Determining the factors that may explain what the data show • Arriving at appropriate research based responses to what the data show (PD, Interventions, programs, resources) • Determining if the responses are or were effective

20. Four guiding questions • Should be a part of each action taken in education • What do the data tell us • Why might that be so • How should we respond • Was our response effective (evaluation)

21. Purposes of the Four guiding questions • Feed a cycle of continuous school improvement • Makes school improvement a continuous process and not an event centered around a certain accreditation event, audit, or other visit • Justify the use of resources for certain programs • Can be used to demonstrate need or to show results • Validate strategies being used or illuminate the need to change

22. Building upon work/sources that have been started/used in the past • Examples but not an exhaustive list • Data guidebook • Data retreat protocols followed in the past • “Data Analysis for Continuous School Improvement” • Victoria Bernhardt

23. Task at hand is to organize various past and present work into a standard, consistent process to be delivered statewide • Will use a model similar to the Nebraska standards for grades K-12 (format and terms used may vary to avoid confusion with content standards) • Standards based on the four guiding questions • Concepts based on specific objectives • Indicators of measureable outcomes • Organized by levels (similar to grade levels)

24. Levels • Each level will go deeper and progressively expand the skills and concepts learned • Each level will involve work in each of the four questions • Complete cycle of data analysis will be completed at each level • Current work is on Level 1 future work will add levels

25. Advantages of standards model • allows • Integration of the training curriculum with the dashboard and other available data tools • Vertical and horizontal expansion of the scope as capacity and expertise are developed • Additional indicators • Additional levels • Distillation of existing formats, sources, and practices

26. Development model • Development group composed of • NDE representatives from various departments • Group of eight professional developers from various ESUs around the state

27. Development group • Meet to bring ideas representative of the practices around the state to the group • Incorporate resources and methods from around the state into a unified presentation • Train professional developers from all ESUs

28. Delivery Model • Once the content is developed • Professional developers from each ESU will be trained • ESU professional developers will deliver training to key district personnel • Key district personnel will deliver the training to the teacher level within the district • Professional developers will follow up with districts and provide assistance with implementation after initial training

29. Archived Materials Training materials will be designed for inclusion in learning management software • ESU use in training districts • District use in training teachers • Personnel review • Availability to use when looking at district’s own data • Online and on demand guided practice

30. Advantages of the delivery model • Allows presentations to smaller groups • Guided practice • Work with live data from the district • Hands on with any technical skills • Allows Coaching, follow up, • and assistance in implementation • Quicker delivery to Nebraska districts

31. Timeline May 2013 Outline of standards (guiding document) presented to ESU PDO Fall 2013 Used in fall CIP workshops Fall 2013 Training of ESU Professional developers Fall 2013/Winter of 2013-2014 Level 1 delivered to districts 2013-2014 and 2014-2015 and beyond Ongoing delivery to teachers in districts Future levels implemented

32. Strengths Collaborative with ESU professional development staff allows the identification of appropriate strategies, Intervention, and Professional Development based on ESU staff expertise Standardized Shared consistent knowledge statewide Sustainable Based on existing staff and resources Measureable Specific standards, concepts and indicators can be evaluated for success Allow follow up on implementation

33. Questions?