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Transcript of Strengthening Measures of College and Career Readiness and Success: State Longitudinal Data Systems,...
Strengthening Measures of College and Career Readiness and Success: State Longitudinal Data Systems,
Governance, & Privacy
March 23, 2015
@CCRSCenter@AYPF_Tweets
#CCRSMeasures
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slides
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• Laura Jimenez, Director, CCRS Center
• Dorothyjean (DJ) Cratty, Senior Researcher, AIR
• Elizabeth Dabney, Associate Director, Research and Policy Analysis, Data Quality Campaign
• Rachel Anderson, Senior Associate, Policy and Advocacy, Data Quality Campaign
• Jean Osumi, Senior Associate for Academic Policy and Evaluation, Hawai‘i P-20/Hawai’i Data Exchange Partnership
• Melissa Beard, Data Governance Coordinator/Higher Education Analyst, Washington Education Research and Data Center (ERDC)
Today’s Presenters
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CCRS CenterWebinar Series: Strengthening Measures of College and Career Readiness and Success
American Institutes for ResearchLaura Jimenez, DirectorMarch 23, 2015
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CCRS Center as a Technical Assistance Hub
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College and Career Readiness and Success Organizer
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CCRS Organizer Outcomes and Measures Strand
Ch. 1 – Specify measurement goals
Ch. 2 – Secure and sustain stakeholder investment
Ch. 3 – Define college and career readiness and success goals and expectations
Ch. 4 – Select measures aligned with these goals and expectations
Measurement Practice Guide
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Goal
Support state education agencies in their expanding use of P-20W state longitudinal data systems to increase college and career readiness and success.
Data Use Series
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College & Career Readiness & Success Center
1000 Thomas Jefferson Street NWWashington, DC 20007800-634-0503www.ccrscenter.org | [email protected]
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Overview of State P20 Data Systems
March 23, 2015
Elizabeth Dabney and Rachel Anderson
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About DQC: Just the Facts
• Nonprofit, nonpartisan, national advocacy organization based in Washington, DC
• Launched in 2005 by 10 founding partners• Partnership network now comprises nearly 100
organizations• Governed by 11-member Board of Directors
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About DQC: Vision and Mission
Vision: DQC envisions an education system in which all stakeholders—from parents to policymakers—are empowered with high-quality data from the early childhood, K–12, postsecondary, and workforce systems to make decisions that ensure every student graduates high school prepared for success in college and the workplace.
Mission: DQC supports state policymakers and other key leaders to promote effective data use to improve student achievement.
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Start with Your Questions
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Start with Your Questions
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What is the graduation rate by high school?
Which early childhood programs best prepare students for kindergarten?
To what degree are high school math grades predictors of readiness for college math?
What industries are most employing high school and college graduates?
How successful are college graduates in the workforce by major or credential?
Early Childhood K-12 Postsecondary Workforce
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10 State Actions for Effective Data Use
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10 State Actions
LINKING P–20W Data1. Link P–20W data systems2. Create stable, sustained support3. Develop governance structures4. Build data repositories
ENSURING DATA ACCESS5. Provide timely data access6. Create individual student progress
reports 7. Create longitudinal reports
BUILDING CAPACITY TO USE DATA8. Develop research agenda 9. Build educator capacity10.Raise awareness of available data
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Data For Action 2011
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Data For Action 2014
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Actions 2011 and 2014
UPDATED 2011 AND 2014 STATE
ACTIONS
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Action 1: Link P–20W data systems
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Action 1: 2011 and 2014
UPDATED 2011 AND 2014 STATE
ACTIONS
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5038
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1927
Number of states in 2011 Number of states in 2014
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Action 3: Develop governance structures
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Action 3: 2011 and 2014
UPDATED 2011 AND 2014 STATE
ACTIONS A cross-agency data governance committee/council is established with authority
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20
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Number of states in 2011 Number of states in 2014
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Key focus areas for high quality implementation of cross-agency data governance
Vision and missionComposition and membershipRoles and responsibilitiesData decisionsCommittee processesSustainability
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Barriers to Ensuring Effective Data Use:“The Four Ts”
Turf: The current culture and structures in education do not support working across
traditional boundaries
Trust: Skepticism about the quality and use of data
persists because data were previously used as a hammer
to punish rather than a flashlight to illuminate
Technical issues: Technical issues remain; however,
solutions are emerging and require the leadership and political will to implement
Time: Competing priorities and scarce resources present challenges to continuing to allocate adequate time to
building and using P20 data systems
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Privacy
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Legislative Activity in the States: 2013
1bill passed related
to student data privacy in
1 state
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Legislative Activity in the States: 2014
110bills related to student data privacy
in 36 states
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Continuing Priorities
• Persistence of some myths (e.g., PARCC) • Concerns about commercialization of data• Congressional action• Increasing demands from districts for
legal/technical support• Concerns about linking data across
systems/sectors• The use of big data and analytics• Unintended consequences from 2014
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Legislative Activity in the States: 2015 As of March 20, most states have introduced privacy legislation.
We have seen more bills introduced in the first half of the 2015 legislative session than in the entire 2014 legislative session.
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States Are Not Wasting Time!
2015 legislation:• Picking up themes from last year: governance,
vendors, Common Core• Strong prohibitions could disrupt key
education services• Some encouraging news too!
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Please use the Questions box to ask questions of our presenters
Questions?
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Hawai‘i Data eXchange PartnershipData Governance
CCRS Center and AYPF webinarMarch 23, 2015
Jean Osumi, EdD
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Infancy to early learning K-12 Postsecondary Workforce
Hawaiʻi Data eXchange Partnership
Kamehameha
Schools(private K-
12)
Hawai‘i private
postsecondariesDept of
Human Services
Dept of Health
GED
Hawai‘i Department of
Education
University of Hawai‘i System
Dept of Labor & Industrial Relations
HCAP Head Start, KCAA Preschools
POTENTIAL NEW DATA SOURCES:
Hawai‘i private
self-insured entities
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Hawaiʻi DXP Underlying Assumptions
• Data used for research, evaluation, and audit purposes to improve the educational and workforce outcomes that benefit the citizens of Hawai‘i– “Pipeline” or “cross-sector” data– De-identified or aggregate data– Personally identified information only
used for matching individuals within and across sectors
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Hawaiʻi Data eXchange Partnership
• General timeline
3-Party Data Sharing MOU (DOE-UH-DLIR)
Added Dept of Health & Dept of Human Services to Data Sharing MOU
Start of Hawaiʻi DXP infrastructure build
1st Qtr: rollout of public reports
2009 2011 2013 2016
2010 2012 2014Act 41 Data Sharing Across State Agencies
Awarded Hoʻokele Grant
4th Qtr: start transitioning Hawaiʻi DXP infrastructure from vendor to UH
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Structure
• 5 Party MOU (Partner agencies)– Hawai‘i State Dept of
Education– University of Hawai‘i System– Dept of Labor & Industrial
Relations– Dept of Health– Dept of Human Services
• Managing partner– Hawai‘i P-20 Partnerships
for Education
Data not currently shared with Hawai‘i DXP
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Data Governance and Access Committee
Data Governance
Process
What data?
How to request data?
Request approval process
Confidentiality training
Request forms
• Initial discussions all about processes
• Process meetings devolved into questions about access to data
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Initial Data Governance Discussions
• Data Access:– Eventually one representative proposed
that Partners should have access to identified data
• No committee member objected to the request
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Regrouping Data Governance
LACK OF UNDERSTANDING OF MOU ASSUMPTIONS
• How do we get everyone on the same page?
ACTION STRATEGY FOR COMMUNICATION AND TRANSPARENCY• Suspended further Data Governance & Access Committee
meetings• Held a series of meetings:
– Internal “data team”– Data governance representatives from Partner agencies
• Prepare for meetings by reading 2009 (3-party) and 2011 (5-party) MOUs– Intent and legal justification for data sharing across agencies
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Data Governance Clarification Meetings • Each group met to document their understanding
of data governance based on the MOUs– Internal “data team” meetings were critical
• Collaborated on a single written data governance document– Fostered “ownership” by Partner data governance
representatives– Built relationships and trust between Partner agencies– Identified each agency’s “hot button” confidentiality
issues
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Data Governance Policy
• Published on Hawai‘i DXP websitehttp://www.hawaiidxp.org/files/Hawaii_DXP_Data_Governance_Policy_2014-03-04.pdf
Includes:– Purpose– Underlying Assumptions– Partner and Affiliate
Definitions/Obligations/Access to Data– Roles & Responsibilities
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Lessons Learned
•The MOUs that establish the data sharing were critical to forming a common vision and understanding of this new resource
Policy First
•There needs to be a “gatekeeper” to enforce the intentions behind the MOUs – particularly around protecting confidentiality and privacy
“Gatekeeper” to Enforce MOU
•Anticipate constant review and changes to policy•e.g.,
role of DXP as only viewing “transition” points
Review and Change
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Please use the Questions box to ask questions of our presenters
Questions?
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P-20W Data Governancein Washington
Melissa Beard, Data Governance CoordinatorMarch 23, 2015
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ERDC created in statute in 2007Mission: To develop longitudinal information spanning the early learning through
workforce system in order to facilitate analyses, provide meaningful reports, collaborate on education research, and share data.
K-12 Postsecondary Education Workforce
Early Learning
Social Services
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Data Governance Structure
Education Research& Data Center
Data Steward Committee
Data Custodian Committee
Research & Reporting Coordination Committee
Office of Financial Management
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Process resulted in an MOU with five principles
• ERDC provides linked, cross-sector data• ERDC maintains the P-20W data warehouse• Protecting privacy of individuals is a priority• Data contributors are the data experts• Common understanding and use of data
increases its value
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Free the data!
• Protecting privacy is paramount• Focus on sharing de-identified data• Data contributors provide advice, not approval• Request process allows for two types of
review, which helps in protecting privacy– Data requests are reviewed by data contributors
prior to data being sent– Requestors provide data contributors report to
review 10 days before going public
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Lessons Learned
• Each agency should have a data governance coordinator, preferably from business
• Data belongs to the state, not program managers
• DG process is to build trust and relationships• Communication was key; monthly large group
and individual meetings• Understand how each partner can benefit
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Questions?
Melissa BeardState of Washington Office of Financial Management
www.erdc.wa.gov
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Please use the Questions box to ask questions of our presenters
Questions?
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• Laura Jimenez, Director, CCRS Center
• Dorothyjean Cratty, Senior Researcher, AIR
• Elizabeth Dabney, Associate Director, Research and Policy Analysis, Data Quality Campaign
• Rachel Anderson, Senior Associate, Policy and Advocacy, Data Quality Campaign
• Jean Osumi, Senior Associate for Academic Policy and Evaluation, Hawai‘i P-20/Hawai’i Data Exchange Partnership
• Melissa Beard, Data Governance Coordinator/Higher Education Analyst, Washington Education Research and Data Center (ERDC)
Questions for our Presenters
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Dorothyjean (DJ) Cratty, Senior Researcher, AIR
Closing Remarks
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Thank you for attending
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