1. THE NEED FOR DATA QUALITY The Oregon DATA Project www.oregondataproject.org

2. A Changing Landscape of Using Data for Student Achievement

3. Collaboration OAESD-ODE-EESC Supporting Progress Toward the Oregon Diploma The Teaching Learning Connection Establishes school-based processes and infrastructure to use data The Growth Project Builds capacity to use and apply longitudinal data The KIDS Project Develops a data structure to streamline data acquisition and reporting The Oregon DATA Project Builds capacity to apply the correct strategies, and to use the correct data at the correct time

4. Input  Guiding question: What do we need to improve the use of data to advance student achievement in Oregon? (Carmichael report)  Statewide approach to training  ESDs deliver regional training  Central repository for student data  Common technical data policies and tools  State policies and leadership

5. Instructional Strands  Strand 1:  Creating a Data Culture: One of Inquiry  Strand 2:  Using Data to Improve Learning in Districts and Schools  Strand 3:  Using Data to Improve Learning in the Classroom

6. Current Status  Stand 1: Creating a Data Culture  All ESDs have certified trainer for Strand 1.  ESDs supporting district needs.  Schedule training through your ESD. As of May 2009: 25 districts

7. Current Status Strand 2: Using Data to Improve Learning in Districts & Schools October: 16 & 17 -- Portland 21 & 22 -- Baker City 23 & 24 -- Pendleton 27 & 28 – Redmond 29 & 30 -- Salem November: 3 & 4 -- Medford 5 & 6 – Eugene December: 9 & 10 - Roseburg Stand 3: Using Data to Improve Student Learning in the Classroom February 9 & 10 -- Baker City 11 & 12 -- Pendleton 23 & 24 -- Redmond 25 & 26 -- Salem March 9 & 10 -- Medford 11 & 12 -- Eugene April 6 & 7 -- Hillsboro 8 & 9 -- Portland As of May 2009: 83 districts 368 participants As of May 2009: 89 districts 585 participants

8. A Changing Landscape of Access to Data

9. Collaboration OAESD-ODE-EESC Supporting Progress Toward the Oregon Diploma The Teaching Learning Connection Establishes school-based processes and infrastructure to use data The Growth Project Builds capacity to use and apply longitudinal data The KIDS Project Develops a data structure to streamline data acquisition and reporting The Oregon DATA Project Builds capacity to apply the correct strategies, and to use the correct data at the correct time

14. OUS System Electronic Transcript Growth Model

15. ? Does the data make me think about my teaching? Does the data make me think about my student’s learning? Does the data provide the support for changes in the teaching/learning process? Does the data lead to improved student achievement? If your answers are NO, then the data are just numbers. The DATA Project’s aim is to make your answers YES!

16. ? From a technical standpoint: Is the data Accurate? Timely? Useful? Secure? Do people have the skills and tool sets to ensure the district has a Culture of Data Quality? DATA Project Technical Training

17. A Changing Need for Quality Data

18. Data Data Data  Instructionally:  More use of data  Data Warehouses will allow instant access to data for decision making.  Data flow across the enterprise will provide access to more data  Accuracy is a must from the start  Accountability:  State Collections gathers required data  Multiple collections, more complex  Accuracy is a must

19. Data Challenges – State Collections  Locating the data source  Local databases  Local spreadsheets  Student Information Systems  Insuring data accuracy  Many times data is stored in multiple locations  Sometimes updated in one but not all locations  How to insure the data is the same – certify data

20. Data Certification  Example: your district’s budget  Identifies how much money is available to spend  Decisions made upon the accuracy of that amount  Monthly reports – certifies the accuracy  Example: your district’s data  Can be used for instructional decisions  Can determine funding and accountability  How often is its accuracy certified?

21. Case in point – IDEA Census  Legacy system v eSIS system  Legacy: 1267 special ed students  eSIS: 1236 special ed students  Which count is correct? See FileSee File  In the end 1333 special ed students $135,000 - $200,000 in funding No errors in case of audit

22. Data Use  Instructional system  DDDM  CIP – SIP  Instructional planning for student achievement  Accountability system  State collections  AYP of NCLB  State Report Card  Many times the same data for different purposes

23. A Model for Improving Data Quality

24. Improving district data – A model  National Forum on Education Statistics  The Forum Curriculum for Improving Education Data: A Resource for Local Education Agencies  National Center for Education Statistics  Forum Guide to Building a Culture of Data Quality: A School and District Resource  Provides a model for districts to consider  Creating a Culture of Data Quality

25. Defining a Culture of Data Quality  It is the belief that good data is an integral part of the educational enterprise.  Everyone in the enterprise demonstrates that shared belief by using appropriate data to achieve the enterprise’s goal of student achievement.  The enterprise is willing to invest resources to obtain quality data  Everyone in the enterprise shows respect for the effort taken to produce quality data

26. Quality Data Culture Components Importance Factors Affecting Timeliness Security Utility Accuracy Policies & Regulations Standards & Guidelines Training & Professional Development Data Entry Environment Timelines & Calendars Technology Roles Data Steward Superintendent Board Member Principal Technology Support Staff Office Staff Teacher More Effective Decision-Making Achieving AYP (Adequate Yearly Progress) Program Funding Other Hardware Software Network

27. Culture of Data Quality  A district commitment  A purposeful assignment of responsibility/oversight Roles Data Steward Superintendent Board Member Principal Technology Support Staff Office Staff Teacher Quality Data Culture

28. Data Steward Responsibilities  Coordinate data collection process  Provide training  Resolve errors  Establish audit procedures  Create Data Collection Calendar  Develop and disseminate data entry standards  Interpret data entry manuals for end-users

29. Data Steward Responsibilities  Collaborate with others (directors of curriculum, special education, assessment, etc.)  Collaborate with the IT Director to enhance computer software for data entry, correction, and auditing  Be the driving force for maintaining the four components of a Culture of Data Quality  Be aware of the complexity and changing nature of the data required for state and federal accountability (State Collections, NCLB, etc.)

30. A Culture of Data Quality  District-wide awareness and support for data quality  Data Quality Oversight Committee/Data Steward?  Responsibility for Culture of Data Quality  Accuracy, Security, Utility, Timeliness  Data Audits and Data Calendar  Training and Policies

31. DATA Project Technical Training  The Need for Data Quality  Data Quality Awareness Presentation  Audience: District leadership  Implementation: Presentations now through COSA  Building a Culture of Data Quality  1-day Workshop District process and materials (4 lessons)  Audience: District implementation leader + District data leader  Implementation: 8 regional ESD workshops starting Fall 2009  Tools and Documents for Data Quality  Web-based training tools and documentation  Audience: District data collection personnel  Implementation: Ongoing development work with ODE

32. What’s in it for you?  Opportunity for in-district discussion that will customize the general model to fit the unique needs of your district.  Internalizes and deepens the model  District and school profile compared to best practices in data management.  Monitoring data error tool can lead to mitigation planning and improvement.  Assured confidence in the data that is generated.

33. Sample Profile DistrictSchool Policies and Regulations2.72.8 Standards and Guidelines 2.92.0 Training and Professional Dev 2.32.0 Timelines and Calendars2.01.8 Technology2.92.0 Data Entry Environment1.82.0 Average 2.432.10 1: Doesn’t happen 3: Usually happens 2: Happens but not the norm 4: Always happens

34. Your Support for this work  Help raise data quality awareness/issues  Encourage your district to send personnel to the Building a Culture of Data Quality workshop  ESDs are encouraged to attend the workshop so they can provide additional district support  Assist in the identification of technical training needs of end-users (Tools and Documents for Data Quality)

35. Building a Culture of Data Quality October and November 2009  8 regional ESDs  Malheur 10/20  Umatilla-Morrow 10/21  Southern Oregon 10/27  Douglas 10/28  High Desert 11/3  Multnomah 11/5  Willamette 11/10  NW Regional 11/17

36. THE OREGON DATA PROJECT TECHNICAL TRAINING STRANDS Direct Access To Achievement www.oregondataproject.org Questions?