P20/W and CTE Contributions to SLDS Implementation—Status of the CTE Work Group Sharon Enright, Ph.D. Associate Director, Office of Career-Technical Education Performance, Data and Accountability Ohio Department of Education 1

The NEW Common Education Data Standards (CEDS) and State Longitudinal Data Systems (SLDS) can support policy and practice. Why should state policymakers and education leaders care? 2

3 1. Stakeholders have important questions they need answered to guide their policies and practices. What are some important questions about CTE?  What are the HS graduation rates of CTE students, compared with non-CTE students? Academic attainment rates?  What percentage of CTE students are earning college credits while still enrolled in high school, compared with non-CTE students?  How do postsecondary enrollment rates of CTE students compare to non-CTE students? Remediation rates?  Are CTE students completing postsecondary studies faster than non- CTE students? How does student debt load compare?  What percentage of CTE students are attaining industry credentials? What difference do credentials make for students in the work place?  What are the employment rates and earnings of CTE students, compared to non-CTE students?

4 2. Increasingly, answering critical questions requires appropriate data to flow efficiently and effectively across systems, sectors, and states. PK-12PostsecondaryWorkforce Critical CTE questions span sectors and states P-20/W Systems (SLDS) Critical CTE questions span sectors and states P-20/W Systems (SLDS) HS Graduation rates? Academic and technical attainment rates? HS Graduation rates? Academic and technical attainment rates? Dual credits? Postsecondary enrollment rates? Remediation rates? Degree (and certificate) attainment and “on-time” rates? Student loan debt load? Dual credits? Postsecondary enrollment rates? Remediation rates? Degree (and certificate) attainment and “on-time” rates? Student loan debt load? Short- and long-term employment rates? Wages? Earnings? In-state Out-of-state Federal & military Adult CTE programs 2-year colleges 4-year colleges Public, private, proprietary

5 2. Increasingly, answering critical questions requires appropriate data to flow efficiently and effectively across systems, sectors, and states. PK-12 & Postsecondary Apprenticeship and Training Programs State and Industry Credentialing Entities Critical CTE questions to address with other sectors P-20/? Systems Critical CTE questions to address with other sectors P-20/? Systems What is the apprenticeship participation rate of CTE students and non-CTE students? Completion rate? Earnings during and after apprenticeship? Student debt load? What is the apprenticeship participation rate of CTE students and non-CTE students? Completion rate? Earnings during and after apprenticeship? Student debt load? What is the state and industry credentialing rate of CTE students and non-CTE students? Do credentials lead to higher earnings? What is the state and industry credentialing rate of CTE students and non-CTE students? Do credentials lead to higher earnings?

6 3. Stakeholders need confidence in the data being used to answer these questions and meet these purposes. Quality Regardless of where and how it was collected, input, and stored Comparability Comparability of data from different systems, allowing us to draw valid comparisons Efficiency Reducing unnecessary wasted time and resources in data collection and sharing

7 Useful CTE Data High Quality GOAL: Quality, comparability and efficient sharing of data to answer critical questions Can Be Shared Efficiently Can Be Compared

8 Meeting these goals requires standardized data The efficient and effective collection, sharing and use of high-quality data by stakeholders at all levels requires standardization of data. Common CTE language. Use of commonly agreed-upon names, definitions, option sets, and technical specifications for a given selection of data elements.

9 Lack of standardization in education data is an unnecessary drain on time, resources and quality Resources are spent duplicating data entries, translating and migrating data across systems, and producing data in multiple formats for various recipients that use a variety of different standards. Vendors are forced to tailor products to each system or state’s specifications increasing time and costs and inhibiting the development of new tools and services. Data quality is reduced because of the risk of error in translating and migrating data. Provision of timely, actionable data to stakeholders is delayed because of the extra time it takes to translate and migrate data. Systems are unable to link data because they cannot spend the resources to conduct the necessary translations or migrations.

10 We’re not standardized… we’re different... Data needs to be standardized!

11 Sometimes we say the same words… …but mean different things. The lack of common definitions won’t help us to standardize…

12 CTE Data Challenges  CTE students and CTE measures are usually “named” the same across states.  CTE students and CTE measures often have different definitions across states.  CTE performance results are likely to be calculated differently across states.

13 Move Toward Standardization: Four-Year “Cohort” Graduation Rate  Federal Education Rules (updated 2008, ESEA) – Beginning in FY2011, states are required to use a four-year cohort graduation rate formula  The rules note that “establishing a uniform and more accurate measure of calculating graduation rate that is comparable across states is a critical and essential step forward in improving high school accountability."  When CTE (in all states) uses the four-year cohort graduation rate formula, we can begin to compare CTE graduation rates across states.

14 CTE Data Can Become More Useful  Graduation Rates (4S1)  Becoming standardized across states (“cohort” graduation rates).  Combination of common data standards and our longitudinal data systems are enabling us to answer “Graduation Rate” questions more effectively.

OHIO PRELIMINARY “Cohort” Graduation Rate: FY2011 CTE Concentrators 15

OHIO PRELIMINARY “Cohort” Graduation Rate: FY2011 CTE Participants 16

OHIO PRELIMINARY “Cohort” Graduation Rate: ALL CTE Participants in Cohort 17

18 OHIO – FY2011 PRELIMINARY “Cohort” Graduation Rate: Disabled and Non-Disabled Students

19 Efforts to standardize education data  The effort to standardize education data has been evolving for decades.  Recent activities to work collaboratively to accelerate the widespread adoption and use of common data standards, and the development of alignment tools, allows for a shift in attention to the USE of data by stakeholders.  CTE is a NEW partner in the education data standardization efforts.

20 SIF & PESC Hand- books RTTA SLDS TSDL State Core SLI Registry Ed-Fi IPEDS EDFacts NEDM Common Core CEDS Data Standards and Initiatives Schools Interoperability Framework Postsecondary Electronic Standards Council

21 SIF and PESC Electronic Standards Marketplace Providers (Vendors) and School Districts Marketplace Providers (Vendors) and Postsecondary Institutions COMMON EDUCATION DATA STANDARDS are needed for electronic exchange of data: Within an educational institution ( Horizontal movement). Between educational institution and State ( Vertical movement). Web standards for the exchange of data are also being developed. SIF and PESC are fully supporting CEDS – Ensuring that all CEDS elements are defined within their electronic standards.

22 Common Education Data Standards (CEDS) Alignment Tool  Sometimes we use different words, but we’re talking about the same thing.  CEDS provides a new ALIGNMENT TOOL to help us with this.

23 Sometimes we say different words but mean the same thing. Are they speaking the same language? Baahahahahhhhhh. Bahahh!

24 Pupil! Student!

CEDS Version Release DateCTE Engagement 1.0 September 2010 CTE not engaged 2.0 January 2012 CTE community participated in public comment periods 3.0January 2013 CTE Work Group Formed (Formally engaged in the process – due to volume of Version 2 CTE public comments.) 25 CEDS Development - CTE Engagement

26 NEW CTE CEDS Working Group First Meeting – May 16, 2012  Melvin D’Souza (Delaware)  Julie Eddy (Colorado)  Sharon Enright (Ohio)  John Haigh (OVAE, Washington, DC)  Phouang Hamilton (Washington)  Matt Hastings (Nebraska)  Dick Ledington (Idaho)  Rhonda Welfare (North Carolina)  Beth Young, Quality Information Partners*  Kathy Chernus, MPR Associates, Inc.  Jim Schoelkopf, MPR Associates, Inc.

27 Data Elements Alignment Tool

28 Four ways to search CEDS data elements

29 Examples of Version 2.0 NEW and UPDATED CTE elements

30 Initial Meeting of the CEDS Version 3.0 CTE Work Group  COMMON CTE DATA DEFINITIONS NEEDED To allow for electronic exchange of data. To compare CTE data across states. To tell a national story about CTE.  SCOPE – Focus on Perkins IV data needs Revise existing CTE elements, as needed. Add new elements as needed for Perkins IV accountability.  OTHER DISCUSSION EXAMPLE – In CEDS, does the term ACADEMIC encompass CTE?

31 SAMPLE of Data Elements Discussed by CEDS Version 3.0 CTE Work Group  CTE Participant – Definition  CTE Concentrator – Definition  Displaced Homemaker – Needs to be Postsecondary more than Secondary.  Nontraditional Participant – Definition  Nontraditional Enrollee – Definition  MORE DATA ELEMENTS WILL BE DISCUSSED.

32 Viewing our work as Applied Research and Analytics  We need to begin to view our work as applied research, using analytics to produce accurate, insightful, actionable, confident real time INSIGHTS.  The new insights, knowledge and predictions we generate will allow for the formation of a “rational basis for action.”  We need to understand that analytic insights are perishable, so timeliness is of the essence.

33 Who’s keeping score? Who’s minding the CTE data? And the data standards? And CTE data analysis? And…