1. How High-Quality IDEA Data Supports Systemic Change in States Dave Phillips, Co-Project Director, Center for IDEA Fiscal Reporting (CIFR) Bill Huennekens, Project Director, Center for the Integration of IDEA Data (CIID), Donna Spiker, Co-Project Director, Center for IDEA Early Childhood Data Systems (DaSy) Tom Fiore, Co-Project Director, IDEA Data Center (IDC) OSEP Project Directors’ Conference August 3, 2016

2. State Data Collection (373) TA Centers ▪ Data TA centers help build state capacity to meet these expectations: ▪ Meet IDEA data reporting requirements ▪ Collect, report, analyze, and utilize high quality IDEA data ▪ Meet IDEA fiscal requirements ▪ Data TA centers help states to develop and enhance state agency data systems

3. State Data Collection (373) TA Centers Provide technical assistance to SEAs to help them meet their federal obligation to collect and report special education fiscal data. Specifically, MFS and LEA MOE Reduction and CEIS. Provides technical assistance to SEAs to increase the capacity to report high quality data required under IDEA Part B 616 and 618 through the integration of IDEA data systems. Assist states with the development or enhancement of data systems for Part C early intervention and Part B preschool special education programs, including support for development of early childhood integrated data systems Provides TA to build state capacity for collecting, reporting, analyzing, and using IDEA data, including building a culture of high-quality data at the state and local levels.

4. Center for IDEA Fiscal Reporting (CIFR)

7. MFS TA Case Study ▪ New team responsible for MFS reporting  Careers in special education, data management, finance and leadership  No existing capacity to apply appropriate data collection and reporting procedures  Lack of awareness of potential consequences  Reporting MFS data for the first time ▪ Initial attempt at calculation: $100 + million shortfall

8. CIFR TA Engagement  On-site with key state staff  Train state staff on requirements  Analyze current and prior reports of funds made available  Assist in understanding from whom and when MFS data is/has been collected (not just the SEA!)  Ensure valid and reliable data collected and reported in current and prior years  Assist in OSEP conversations as needed/requested by state  Assist with development of written policies, procedures and practices for future MFS data collections

9. Initial Impact  SEA staff demonstrate increased understanding of requirements and development of capacity to collect and report MFS data  SEA staff increase ability to communicate to legislative and executive branches about the requirements  Valid and reliable data show drastically reduced MFS shortfall Foundation for program improvement efforts

10. Center for the Integration of IDEA Data (CIID)

11. What is an Integrated Data System? A data system that integrates data across programs and sectors provides a rich source of information for program administrators, school leaders, researchers, and policymakers to understand what works and how to invest resources to improve the outcomes for children with disabilities.

12. Benefits of Data Integration ▪ Efficiency ▪ Single source for reporting ▪ Reduces duplication of effort ▪ Data validation ▪ Program staff can focus on additional data/reporting needs

13. Benefits of Data Integration ▪ Sustainability ▪ Information for Decision Making ▪ Validity, reliability of data ▪ Cross-program Analysis ▪ Increased Use of SLDS ▪ More SEA program users ▪ More use cases for SLDS (reports)

14. Beginning Data Integration – build a use case ▪ Establish goal/purpose for integration ▪ Identify the datasets or systems to integrate ▪ Ensure common understanding amongst key stakeholders

15. Importance of establishing a use case ▪ Identify champions to support integration efforts ▪ Identify challengers and develop plan to address concerns

16. The Center for IDEA Early Childhood Data Systems (DaSy)

17. DaSy’s Topic Cohorts: A New Way To Deliver TA ▪ Features of topic cohorts: ▪ TA focused on a specific topic ▪ Intensive TA work with a state team ▪ Intended to result in measurable systemic change around quality data and data systems ▪ Outcomes ▪ Common outcomes for the topic cohort ▪ Individualized outcomes for each state ▪ Includes both individual TA and cross-state learning opportunities

18. DaSy’s Topic Cohorts: A New Way To Deliver TA (cont) ▪ States apply to be part of cohort ▪ Span 12-18 months ▪ Guided by written TA agreement ▪ Not just a Learning Community model ▪ States complete sections of ECTA Framework (which includes DaSy Framework) self-assessment. ▪ One cohort using adaptations of portions of the ECIDs Toolkit.

19. What is a topic cohort? ▪ Designed to result in measureable systemic change ▪ Involves extensive work with state ▪ Spans a duration of many months ▪ Based on a TA plan developed jointly with state ▪ Will make use of the framework ▪ Could be delivered collaboratively with one or more other Centers ▪ Involves 1 on 1 work with state (e.g., phone, email, onsite ▪ Involves formation of a learning community with small group of states with an interest in the same topic ▪ Involves group TA (e.g., onsite meetings, webinars, group calls)

20. How are topic cohorts designed? ▪ Cohorts are designed and implemented through cross-center TA teams lead by 2 co-leads ▪ Coordination of the cohorts is accomplished through DaSy and ECTA leadership teams ▪ Cross-State TA Activities: ▪ Bi-monthly cross-state webinars ▪ Up to two face-to-face meetings per cohort ▪ Mechanisms for sharing resources and tools ▪ Individualized Intensive TA Activities: ▪ Based on the state’s TA agreement ▪ Delivered by a 2-person TA team ▪ Additional TA is accessed as needed ▪ Individualized in-person TA provided onsite in states as needed

21. Example: Including IFSPs in Your Data System ▪ Outcomes: Develop and implement a plan for including IFSP data in a state data system Understand the technical considerations for adding IFSP data to an existing data system Identify the strengths and limitations of web-based data systems that allow for real-time collection and analysis of IFSP data Identify and answer critical questions Participating state Part C programs: CT, DE, KS, MA, MS, VA, WA

22. Some individual state goals for this topic cohort include… ▪ Identify critical questions state wants to address with IFSP data ▪ Identify systems requirements and functionality for electronic IFSP, including legal and privacy issues ▪ Determine how to integrate child outcomes data into IFSP ▪ Learn about other states’ criteria and tools to evaluate IFSP quality ▪ Enhance current data system used to collect IFSP and other data ▪ Identify reports to be developed for local programs’ use

23. IDEA Data Center (IDC)

24. High-quality evaluation data are essential for effecting systemic changes ▪ A shared vision of an outcome state guides a reform ▪ Systemic reform is a process that requires continuous adjustment and correction ▪ Leaders and participants monitor progress toward the desired outcome state (fulfilling the vision), and modify reform efforts when needed ▪ Data-based modifications to the vision or restructuring organizations and systems is often necessary to increase the opportunity to achieve the vision

25. Functions necessary to effect systemic changes ▪ Needs assessment and prioritization ▪ Vision and purpose-setting ▪ Planning and decision-making ▪ Implementation ▪ Evaluation

26. Evaluative information used to adjust plans, activities, and management ▪ Evaluative information used to determine the worth or value of actions and activities vis-à-vis the desired outcome state ▪ Determinations of the worth of actions and activities used to alter plans and management processes ▪ Reflections on the worth of actions and activities used to modify the vision/purpose, and make alterations to organizational structures and management processes

27. Use of evaluation data for effecting systemic changes I. Improved System Function Feedback 1 Feedback 2 Feedforward Worth Reflec- tion Outcome State III. Improved Child/Family Outcomes II. Scaling- Up of Practices Needs Assessment and Prioritization Functions Vision and Purpose-Setting Functions Implementation Functions Evaluation Functions  Embedded Inquiry  Formal Evaluation Planning and Decision- Making Functions

28. Discussion

29. Discussion Questions ▪ What else can we do to help address challenges in collecting and reporting high quality IDEA data? ▪ In the center(s) you direct or grants you oversee, what is your view of using IDEA data to improve child outcomes?

30. Where Can You Find Us? CIFRhttp://cifr.wested.org/http://cifr.wested.org/ CIIDhttps://ciidta.grads360.orghttps://ciidta.grads360.org DaSydasycenter.orgdasycenter.org IDChttp://ideadata.org/http://ideadata.org/