SlideShare a Scribd company logo
1 of 23
Common Education Data
     Standards

    Content in Context Metadata Lab
               June 2012

             Jack Buckley
            Commissioner,
 National Center for Education Statistics
Here’s a           Hmmm…
   new student:     Did you mean:

     Matthe           Matthew ?
    SmithIII           Smith ?
Race = Guamanian   Suffix = III ?
   Gender = M      Race = NHOPI ?
                      Sex = M ?
What is CEDS?
• A national collaborative effort to develop
  voluntary, common data standards for a key
  set of education data elements
• A vocabulary including standard
  definitions, option sets & technical
  specifications to streamline sharing and
  comparing
Voluntary Common Vocabulary
Why do we need CEDS?
1. Accurate, timely, and consistent data
   to inform decisionmaking
2. Share&compare high quality data within
   & across P-20 sectors
CEDS is Not:
   Required
   All or nothing

   A data collection

  An implementation

   Solely an ED undertaking

   A federal unit record system
How do we get it done?
• Assemble stakeholders representing the field
• Use existing sources of standards
• Check alignment with the field
• Review ideas with the public
• Model elements
• Place in tools
• Release
Version 1
• Released in September, 2010
• 161 elements – focused on K-12
  – Student record exchange across
    districts/States
  – Student transcripts
  – High school feedback reports from
    postsecondary to K-12
Version 2
• Released in January, 2012
• Expansion of elements and stakeholders
  •  Added early learning
   • Changing focus of postsecondary beyond
     K12 transitions
   • Massive growth of K-12 elements
• Development of Logical Data Model
• Tools: Data Alignment Policy Questions
CEDS v2 Stakeholders (1 of 2)
• State Agencies
   o   State Education Agencies
   o   State Higher Education Agencies
   o   Social Services Agencies
• Local Education Agencies
   o   K12
   o   Head Start
   o   Social Services
• Institutions of Higher Education
   o   Public
   o   Private
   o   Community Colleges
CEDS v2 Stakeholders (2 of 2)
• U.S. Department of Education
  o   NCES (SLDS, IPEDS)           o   Financial Student Aid
  o   EDFacts                      o   Office of the Undersecretary
  o   Office of Educ. Technology   o   Special Education

• U.S. Health and Human Services
• U.S. Department of Labor
• Interoperability Standard Organizations
• Education Associations
• Foundations
Standard Information: The Basics

                        Element
                        Definition


         Hispanic
         or Latino      Option set
         Ethnicity

          Yes
          No
          NotSelected
                         Domain      K12
                         Entity            K12 Student




               Related Use Cases
CEDS Logical Data Model
• Provides a high-level framework for
 translating standards into physical models
• System-agnostic representation
• 2 distinct views:
  • Domain Entity Schema
  • Normalized Data Schema
Entity Relationship Diagram (ERD)
CEDS Align
•Web-based tool that allows users to:
• Import or input their data dictionaries
• Align their data to CEDS
• Compare themselves with others
• Analyze their data in
relation to various other
CEDS-aligned efforts
CEDS Connect (Upcoming)
Builds on the CEDS Align tool and allows
stakeholders to:
• Generate specific and relevant maps to
a growing pool of CEDS connections
Version 3 Content Areas
• Early Learning
• K12
• Postsecondary
• Workforce
• Career and Technical
  Education
• Adult Education
• Race to the Top Assessments
K12 Development Work
• Teaching and Learning – Formative
  Assessments
• Supporting Teaching and Learning
  Initiatives
• Portable Student Records
• RTTA Consortia Support
Unpacking the model                                                            What data
                                                                             elements and
                                                                          structures need to
                                                                              be added to
            What process                                                         CEDS?
           measures should                         Formative
            become CEDS                           Assessment
             elements?
     Formative
     Feedback
                                   What additional
 measured output                    data elements
                        -
                                   error Instructional
                         measureddescribe learning
                       +                 Decisions                Related content
                                                                             Learner
 reference                        progressions, etc.?
                                                                     metadata to
                                                                 Learner
  Standards                                     Adjusted:                    Competencies
                                                                   include, or not
  Learning Progressions                         Instruction,                 (less variable)
  Current Learning Goals                                           (for CEDS v3)?
  Criteria for Success                          Activities,
  Curriculum, Unit & Lesson Plans               Practice
 Activities, Resources
                                             (variable inputs)
Race to the Top Assessments
• Assessment Interoperability Framework (AIF)
• Identify Changes to Existing CEDS/Develop
  CEDS Assessment Data Elements
• Beyond Data Elements and Data Model
• AIF Best Practice Guidance
• Prototype Demonstration
• Integrate into CEDS, including updated data
  model and tools
Race to the Top Assessments

More Related Content

What's hot

Semantic Analysis for Curricular Mapping, Gap Analysis & Remediation
Semantic Analysis for Curricular Mapping, Gap Analysis & RemediationSemantic Analysis for Curricular Mapping, Gap Analysis & Remediation
Semantic Analysis for Curricular Mapping, Gap Analysis & RemediationJennifer Staley, M.Ed., CPLP
 
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...CITE
 
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, TurkeyAn insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkeystrehlst
 
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)Jennifer Staley
 
Xiao Hu "Learning Analytics Initiatives"
Xiao Hu "Learning Analytics Initiatives"Xiao Hu "Learning Analytics Initiatives"
Xiao Hu "Learning Analytics Initiatives"CITE
 
Educational Data Mining/Learning Analytics issue brief overview
Educational Data Mining/Learning Analytics issue brief overviewEducational Data Mining/Learning Analytics issue brief overview
Educational Data Mining/Learning Analytics issue brief overviewMarie Bienkowski
 
Data Mining for Higher Education
Data Mining for Higher EducationData Mining for Higher Education
Data Mining for Higher EducationSalford Systems
 
Revised bookpresentation videodec2014
Revised bookpresentation videodec2014Revised bookpresentation videodec2014
Revised bookpresentation videodec2014Patricia Wadman
 
Izobrazevanje za data-mining
Izobrazevanje za data-miningIzobrazevanje za data-mining
Izobrazevanje za data-miningbutest
 
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"CITE
 
Advances in Learning Analytics and Educational Data Mining
Advances in Learning Analytics and Educational Data Mining Advances in Learning Analytics and Educational Data Mining
Advances in Learning Analytics and Educational Data Mining MehrnooshV
 
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVE
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVEDATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVE
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVEIJDKP
 
Hadoop infrastructure for education
Hadoop infrastructure for educationHadoop infrastructure for education
Hadoop infrastructure for educationDarko Marjanovic
 
X api introduction and acrossx solution (1)
X api introduction and acrossx solution (1)X api introduction and acrossx solution (1)
X api introduction and acrossx solution (1)Jessie Chuang
 
2008 regional educational laboratory board of directors (rel midwest)
2008 regional educational laboratory board of directors (rel midwest) 2008 regional educational laboratory board of directors (rel midwest)
2008 regional educational laboratory board of directors (rel midwest) Christopher Thorn
 
Overview of Radiant Modules
Overview of Radiant ModulesOverview of Radiant Modules
Overview of Radiant ModulesWendy Colby
 

What's hot (19)

Semantic Analysis for Curricular Mapping, Gap Analysis & Remediation
Semantic Analysis for Curricular Mapping, Gap Analysis & RemediationSemantic Analysis for Curricular Mapping, Gap Analysis & Remediation
Semantic Analysis for Curricular Mapping, Gap Analysis & Remediation
 
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...
Xiao Hu "Overview of the Space of Learning Analytics and Educational Data Min...
 
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, TurkeyAn insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey
An insight into Educational Data Mining at Muğla Sıtkı Koçman University, Turkey
 
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)
Using Semantic Analysis for Curricular Alignment (Sloan-C Presentation)
 
Xiao Hu "Learning Analytics Initiatives"
Xiao Hu "Learning Analytics Initiatives"Xiao Hu "Learning Analytics Initiatives"
Xiao Hu "Learning Analytics Initiatives"
 
Educational Data Mining/Learning Analytics issue brief overview
Educational Data Mining/Learning Analytics issue brief overviewEducational Data Mining/Learning Analytics issue brief overview
Educational Data Mining/Learning Analytics issue brief overview
 
DEMYSTIFYING EVIDENCE IN EDTECH
DEMYSTIFYING EVIDENCE IN EDTECHDEMYSTIFYING EVIDENCE IN EDTECH
DEMYSTIFYING EVIDENCE IN EDTECH
 
LRMI in Context, Brandt Redd
LRMI in Context, Brandt ReddLRMI in Context, Brandt Redd
LRMI in Context, Brandt Redd
 
Data Mining for Higher Education
Data Mining for Higher EducationData Mining for Higher Education
Data Mining for Higher Education
 
Revised bookpresentation videodec2014
Revised bookpresentation videodec2014Revised bookpresentation videodec2014
Revised bookpresentation videodec2014
 
Izobrazevanje za data-mining
Izobrazevanje za data-miningIzobrazevanje za data-mining
Izobrazevanje za data-mining
 
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"
Gobert, Dede, Martin, Rose "Panel: Learning Analytics and Learning Sciences"
 
Advances in Learning Analytics and Educational Data Mining
Advances in Learning Analytics and Educational Data Mining Advances in Learning Analytics and Educational Data Mining
Advances in Learning Analytics and Educational Data Mining
 
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVE
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVEDATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVE
DATA MINING IN EDUCATION : A REVIEW ON THE KNOWLEDGE DISCOVERY PERSPECTIVE
 
Hadoop infrastructure for education
Hadoop infrastructure for educationHadoop infrastructure for education
Hadoop infrastructure for education
 
X api introduction and acrossx solution (1)
X api introduction and acrossx solution (1)X api introduction and acrossx solution (1)
X api introduction and acrossx solution (1)
 
Too Difficult
Too DifficultToo Difficult
Too Difficult
 
2008 regional educational laboratory board of directors (rel midwest)
2008 regional educational laboratory board of directors (rel midwest) 2008 regional educational laboratory board of directors (rel midwest)
2008 regional educational laboratory board of directors (rel midwest)
 
Overview of Radiant Modules
Overview of Radiant ModulesOverview of Radiant Modules
Overview of Radiant Modules
 

Similar to Common Education Data Standards, Jack Buckley

Architecting Academic Intelligence
Architecting Academic IntelligenceArchitecting Academic Intelligence
Architecting Academic IntelligenceBrendan Aldrich
 
2015 CIC: #EdTech Forum - Common Education Data
2015 CIC: #EdTech Forum - Common Education Data2015 CIC: #EdTech Forum - Common Education Data
2015 CIC: #EdTech Forum - Common Education DataAAP PreK-12 Learning Group
 
IIS IT Directors Update
IIS IT Directors UpdateIIS IT Directors Update
IIS IT Directors Updatedgoodman_1958
 
Data Visualization and Growth
Data Visualization and GrowthData Visualization and Growth
Data Visualization and GrowthSteven Arnoff
 
Desire2Learn Analytics Oklahoma RUF
Desire2Learn Analytics Oklahoma RUFDesire2Learn Analytics Oklahoma RUF
Desire2Learn Analytics Oklahoma RUFBarry Dahl
 
From Data To Information Perspectives On Policy And Practice
From Data To Information  Perspectives On Policy And PracticeFrom Data To Information  Perspectives On Policy And Practice
From Data To Information Perspectives On Policy And PracticeJeff_Watson
 
2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...Christopher Thorn
 
2010 nces management information systems conference when world collide
2010 nces  management information systems conference   when world collide2010 nces  management information systems conference   when world collide
2010 nces management information systems conference when world collideChristopher Thorn
 
Data warehouse 101-fundamentals-
Data warehouse 101-fundamentals-Data warehouse 101-fundamentals-
Data warehouse 101-fundamentals-AshishGuleria
 
NCME Big Data in Education
NCME Big Data  in EducationNCME Big Data  in Education
NCME Big Data in EducationPhilip Piety
 
Coit20247 database design and development
Coit20247   database design and developmentCoit20247   database design and development
Coit20247 database design and developmentSandeep Ratnam
 
SC Assessment Summit March 2013
SC Assessment Summit March 2013SC Assessment Summit March 2013
SC Assessment Summit March 2013NWEA
 
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)Shane Dawson
 
Sda and staff eval2
Sda and staff eval2Sda and staff eval2
Sda and staff eval2tamraranard
 
Datato information5 21-final519pm
Datato information5 21-final519pmDatato information5 21-final519pm
Datato information5 21-final519pmSETDA
 
Jisc learning analytics service overview Aug 2018
Jisc learning analytics service overview Aug 2018Jisc learning analytics service overview Aug 2018
Jisc learning analytics service overview Aug 2018Paul Bailey
 
Introduction to Data Science - Week 3 - Steps involved in Data Science
Introduction to Data Science - Week 3 - Steps involved in Data ScienceIntroduction to Data Science - Week 3 - Steps involved in Data Science
Introduction to Data Science - Week 3 - Steps involved in Data ScienceFerdin Joe John Joseph PhD
 
Data Driven School : MIS case study on Schools of USA
Data Driven School : MIS case study on Schools of USAData Driven School : MIS case study on Schools of USA
Data Driven School : MIS case study on Schools of USAMoshiur Rahman Moshi
 
Edu 653 power point h. aldrich
Edu 653 power point h. aldrichEdu 653 power point h. aldrich
Edu 653 power point h. aldrichrich1hm
 
Week One - Why Data?
Week One - Why Data?Week One - Why Data?
Week One - Why Data?Rich Parker
 

Similar to Common Education Data Standards, Jack Buckley (20)

Architecting Academic Intelligence
Architecting Academic IntelligenceArchitecting Academic Intelligence
Architecting Academic Intelligence
 
2015 CIC: #EdTech Forum - Common Education Data
2015 CIC: #EdTech Forum - Common Education Data2015 CIC: #EdTech Forum - Common Education Data
2015 CIC: #EdTech Forum - Common Education Data
 
IIS IT Directors Update
IIS IT Directors UpdateIIS IT Directors Update
IIS IT Directors Update
 
Data Visualization and Growth
Data Visualization and GrowthData Visualization and Growth
Data Visualization and Growth
 
Desire2Learn Analytics Oklahoma RUF
Desire2Learn Analytics Oklahoma RUFDesire2Learn Analytics Oklahoma RUF
Desire2Learn Analytics Oklahoma RUF
 
From Data To Information Perspectives On Policy And Practice
From Data To Information  Perspectives On Policy And PracticeFrom Data To Information  Perspectives On Policy And Practice
From Data To Information Perspectives On Policy And Practice
 
2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...
 
2010 nces management information systems conference when world collide
2010 nces  management information systems conference   when world collide2010 nces  management information systems conference   when world collide
2010 nces management information systems conference when world collide
 
Data warehouse 101-fundamentals-
Data warehouse 101-fundamentals-Data warehouse 101-fundamentals-
Data warehouse 101-fundamentals-
 
NCME Big Data in Education
NCME Big Data  in EducationNCME Big Data  in Education
NCME Big Data in Education
 
Coit20247 database design and development
Coit20247   database design and developmentCoit20247   database design and development
Coit20247 database design and development
 
SC Assessment Summit March 2013
SC Assessment Summit March 2013SC Assessment Summit March 2013
SC Assessment Summit March 2013
 
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)
A-LASI Getting started in learning analytics (Lockyer, Rogers and Dawson)
 
Sda and staff eval2
Sda and staff eval2Sda and staff eval2
Sda and staff eval2
 
Datato information5 21-final519pm
Datato information5 21-final519pmDatato information5 21-final519pm
Datato information5 21-final519pm
 
Jisc learning analytics service overview Aug 2018
Jisc learning analytics service overview Aug 2018Jisc learning analytics service overview Aug 2018
Jisc learning analytics service overview Aug 2018
 
Introduction to Data Science - Week 3 - Steps involved in Data Science
Introduction to Data Science - Week 3 - Steps involved in Data ScienceIntroduction to Data Science - Week 3 - Steps involved in Data Science
Introduction to Data Science - Week 3 - Steps involved in Data Science
 
Data Driven School : MIS case study on Schools of USA
Data Driven School : MIS case study on Schools of USAData Driven School : MIS case study on Schools of USA
Data Driven School : MIS case study on Schools of USA
 
Edu 653 power point h. aldrich
Edu 653 power point h. aldrichEdu 653 power point h. aldrich
Edu 653 power point h. aldrich
 
Week One - Why Data?
Week One - Why Data?Week One - Why Data?
Week One - Why Data?
 

More from AAP PreK-12 Learning Group

2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards
2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards
2015 CIC: #EdTech Forum - Understanding and Influencing Publishing StandardsAAP PreK-12 Learning Group
 
2015 CIC: #EdTech Forum - Data Privacy Standards
2015 CIC: #EdTech Forum - Data Privacy Standards2015 CIC: #EdTech Forum - Data Privacy Standards
2015 CIC: #EdTech Forum - Data Privacy StandardsAAP PreK-12 Learning Group
 
LRMI: Using Education Metadata to Support Learning
LRMI: Using Education Metadata to Support LearningLRMI: Using Education Metadata to Support Learning
LRMI: Using Education Metadata to Support LearningAAP PreK-12 Learning Group
 
Dynamic Metadata: Remixing Content | Education Metadata Meetup
Dynamic Metadata: Remixing Content | Education Metadata MeetupDynamic Metadata: Remixing Content | Education Metadata Meetup
Dynamic Metadata: Remixing Content | Education Metadata MeetupAAP PreK-12 Learning Group
 
Metadata Sandboxing | Education Metadata Meetup
Metadata Sandboxing | Education Metadata MeetupMetadata Sandboxing | Education Metadata Meetup
Metadata Sandboxing | Education Metadata MeetupAAP PreK-12 Learning Group
 
Smithsonian Show & Tell | Education Metadata Meetup
Smithsonian Show & Tell | Education Metadata MeetupSmithsonian Show & Tell | Education Metadata Meetup
Smithsonian Show & Tell | Education Metadata MeetupAAP PreK-12 Learning Group
 
Building for Efficacy at Pearson | Education Metadata Meetup
Building for Efficacy at Pearson | Education Metadata MeetupBuilding for Efficacy at Pearson | Education Metadata Meetup
Building for Efficacy at Pearson | Education Metadata MeetupAAP PreK-12 Learning Group
 
BrainPOP LRMI Case Study | Education Metadata Meetup
BrainPOP LRMI Case Study | Education Metadata MeetupBrainPOP LRMI Case Study | Education Metadata Meetup
BrainPOP LRMI Case Study | Education Metadata MeetupAAP PreK-12 Learning Group
 
Leveraging Metadata in K12 | Education Metadata Meetup
Leveraging Metadata in K12 | Education Metadata MeetupLeveraging Metadata in K12 | Education Metadata Meetup
Leveraging Metadata in K12 | Education Metadata MeetupAAP PreK-12 Learning Group
 
Helping Educational Content Reach Intended Audiences | Education Metadata Meetup
Helping Educational Content Reach Intended Audiences | Education Metadata MeetupHelping Educational Content Reach Intended Audiences | Education Metadata Meetup
Helping Educational Content Reach Intended Audiences | Education Metadata MeetupAAP PreK-12 Learning Group
 
Integrating Metadata into WISE Learn | Education Metadata Meetup
Integrating Metadata into WISE Learn | Education Metadata MeetupIntegrating Metadata into WISE Learn | Education Metadata Meetup
Integrating Metadata into WISE Learn | Education Metadata MeetupAAP PreK-12 Learning Group
 
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...ISLE Open Education Resources Enabling Open Access and Integration | Educatio...
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...AAP PreK-12 Learning Group
 
Intel Education on the Need for Standards | Education Metadata Meetup
Intel Education on the Need for Standards | Education Metadata MeetupIntel Education on the Need for Standards | Education Metadata Meetup
Intel Education on the Need for Standards | Education Metadata MeetupAAP PreK-12 Learning Group
 

More from AAP PreK-12 Learning Group (20)

2015 #EdTech Forum at CIC: xAPI
2015 #EdTech Forum at CIC: xAPI2015 #EdTech Forum at CIC: xAPI
2015 #EdTech Forum at CIC: xAPI
 
2015 CIC: #EdTech Forum - Accessibility
2015 CIC: #EdTech Forum - Accessibility2015 CIC: #EdTech Forum - Accessibility
2015 CIC: #EdTech Forum - Accessibility
 
2015 CIC: #EdTech Forum - EPUB3
2015 CIC: #EdTech Forum - EPUB32015 CIC: #EdTech Forum - EPUB3
2015 CIC: #EdTech Forum - EPUB3
 
2015 CIC: #EdTech Forum - SBAC
2015 CIC: #EdTech Forum - SBAC2015 CIC: #EdTech Forum - SBAC
2015 CIC: #EdTech Forum - SBAC
 
2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards
2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards
2015 CIC: #EdTech Forum - Understanding and Influencing Publishing Standards
 
2015 CIC: #EdTech Forum - Data Privacy Standards
2015 CIC: #EdTech Forum - Data Privacy Standards2015 CIC: #EdTech Forum - Data Privacy Standards
2015 CIC: #EdTech Forum - Data Privacy Standards
 
2015 CIC: #EdTech Forum - LRMI
2015 CIC: #EdTech Forum - LRMI2015 CIC: #EdTech Forum - LRMI
2015 CIC: #EdTech Forum - LRMI
 
LRMI: Using Education Metadata to Support Learning
LRMI: Using Education Metadata to Support LearningLRMI: Using Education Metadata to Support Learning
LRMI: Using Education Metadata to Support Learning
 
MERLOT | Education Metadata Meetup
MERLOT | Education Metadata MeetupMERLOT | Education Metadata Meetup
MERLOT | Education Metadata Meetup
 
Dynamic Metadata: Remixing Content | Education Metadata Meetup
Dynamic Metadata: Remixing Content | Education Metadata MeetupDynamic Metadata: Remixing Content | Education Metadata Meetup
Dynamic Metadata: Remixing Content | Education Metadata Meetup
 
Metadata Sandboxing | Education Metadata Meetup
Metadata Sandboxing | Education Metadata MeetupMetadata Sandboxing | Education Metadata Meetup
Metadata Sandboxing | Education Metadata Meetup
 
LRMI & NYPL | Education Metadata Meetup
LRMI & NYPL | Education Metadata MeetupLRMI & NYPL | Education Metadata Meetup
LRMI & NYPL | Education Metadata Meetup
 
Smithsonian Show & Tell | Education Metadata Meetup
Smithsonian Show & Tell | Education Metadata MeetupSmithsonian Show & Tell | Education Metadata Meetup
Smithsonian Show & Tell | Education Metadata Meetup
 
Building for Efficacy at Pearson | Education Metadata Meetup
Building for Efficacy at Pearson | Education Metadata MeetupBuilding for Efficacy at Pearson | Education Metadata Meetup
Building for Efficacy at Pearson | Education Metadata Meetup
 
BrainPOP LRMI Case Study | Education Metadata Meetup
BrainPOP LRMI Case Study | Education Metadata MeetupBrainPOP LRMI Case Study | Education Metadata Meetup
BrainPOP LRMI Case Study | Education Metadata Meetup
 
Leveraging Metadata in K12 | Education Metadata Meetup
Leveraging Metadata in K12 | Education Metadata MeetupLeveraging Metadata in K12 | Education Metadata Meetup
Leveraging Metadata in K12 | Education Metadata Meetup
 
Helping Educational Content Reach Intended Audiences | Education Metadata Meetup
Helping Educational Content Reach Intended Audiences | Education Metadata MeetupHelping Educational Content Reach Intended Audiences | Education Metadata Meetup
Helping Educational Content Reach Intended Audiences | Education Metadata Meetup
 
Integrating Metadata into WISE Learn | Education Metadata Meetup
Integrating Metadata into WISE Learn | Education Metadata MeetupIntegrating Metadata into WISE Learn | Education Metadata Meetup
Integrating Metadata into WISE Learn | Education Metadata Meetup
 
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...ISLE Open Education Resources Enabling Open Access and Integration | Educatio...
ISLE Open Education Resources Enabling Open Access and Integration | Educatio...
 
Intel Education on the Need for Standards | Education Metadata Meetup
Intel Education on the Need for Standards | Education Metadata MeetupIntel Education on the Need for Standards | Education Metadata Meetup
Intel Education on the Need for Standards | Education Metadata Meetup
 

Recently uploaded

Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Sapana Sha
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDThiyagu K
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfagholdier
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...fonyou31
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityGeoBlogs
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...Sapna Thakur
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfchloefrazer622
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxVishalSingh1417
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpinRaunakKeshri1
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Krashi Coaching
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfsanyamsingh5019
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024Janet Corral
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphThiyagu K
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfchloefrazer622
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Celine George
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfciinovamais
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxiammrhaywood
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxheathfieldcps1
 

Recently uploaded (20)

Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111Call Girls in Dwarka Mor Delhi Contact Us 9654467111
Call Girls in Dwarka Mor Delhi Contact Us 9654467111
 
Measures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SDMeasures of Dispersion and Variability: Range, QD, AD and SD
Measures of Dispersion and Variability: Range, QD, AD and SD
 
Holdier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdfHoldier Curriculum Vitae (April 2024).pdf
Holdier Curriculum Vitae (April 2024).pdf
 
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
Ecosystem Interactions Class Discussion Presentation in Blue Green Lined Styl...
 
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"Mattingly "AI & Prompt Design: The Basics of Prompt Design"
Mattingly "AI & Prompt Design: The Basics of Prompt Design"
 
Paris 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activityParis 2024 Olympic Geographies - an activity
Paris 2024 Olympic Geographies - an activity
 
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
BAG TECHNIQUE Bag technique-a tool making use of public health bag through wh...
 
Disha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdfDisha NEET Physics Guide for classes 11 and 12.pdf
Disha NEET Physics Guide for classes 11 and 12.pdf
 
Unit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptxUnit-IV- Pharma. Marketing Channels.pptx
Unit-IV- Pharma. Marketing Channels.pptx
 
Student login on Anyboli platform.helpin
Student login on Anyboli platform.helpinStudent login on Anyboli platform.helpin
Student login on Anyboli platform.helpin
 
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
Kisan Call Centre - To harness potential of ICT in Agriculture by answer farm...
 
Sanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdfSanyam Choudhary Chemistry practical.pdf
Sanyam Choudhary Chemistry practical.pdf
 
General AI for Medical Educators April 2024
General AI for Medical Educators April 2024General AI for Medical Educators April 2024
General AI for Medical Educators April 2024
 
Z Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot GraphZ Score,T Score, Percential Rank and Box Plot Graph
Z Score,T Score, Percential Rank and Box Plot Graph
 
Arihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdfArihant handbook biology for class 11 .pdf
Arihant handbook biology for class 11 .pdf
 
Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17Advanced Views - Calendar View in Odoo 17
Advanced Views - Calendar View in Odoo 17
 
Activity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdfActivity 01 - Artificial Culture (1).pdf
Activity 01 - Artificial Culture (1).pdf
 
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptxSOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
SOCIAL AND HISTORICAL CONTEXT - LFTVD.pptx
 
The basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptxThe basics of sentences session 2pptx copy.pptx
The basics of sentences session 2pptx copy.pptx
 
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptxINDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
INDIA QUIZ 2024 RLAC DELHI UNIVERSITY.pptx
 

Common Education Data Standards, Jack Buckley

  • 1. Common Education Data Standards Content in Context Metadata Lab June 2012 Jack Buckley Commissioner, National Center for Education Statistics
  • 2. Here’s a Hmmm… new student: Did you mean: Matthe Matthew ? SmithIII Smith ? Race = Guamanian Suffix = III ? Gender = M Race = NHOPI ? Sex = M ?
  • 3. What is CEDS? • A national collaborative effort to develop voluntary, common data standards for a key set of education data elements • A vocabulary including standard definitions, option sets & technical specifications to streamline sharing and comparing Voluntary Common Vocabulary
  • 4. Why do we need CEDS? 1. Accurate, timely, and consistent data to inform decisionmaking 2. Share&compare high quality data within & across P-20 sectors
  • 5. CEDS is Not: Required All or nothing A data collection An implementation Solely an ED undertaking A federal unit record system
  • 6. How do we get it done? • Assemble stakeholders representing the field • Use existing sources of standards • Check alignment with the field • Review ideas with the public • Model elements • Place in tools • Release
  • 7. Version 1 • Released in September, 2010 • 161 elements – focused on K-12 – Student record exchange across districts/States – Student transcripts – High school feedback reports from postsecondary to K-12
  • 8. Version 2 • Released in January, 2012 • Expansion of elements and stakeholders • Added early learning • Changing focus of postsecondary beyond K12 transitions • Massive growth of K-12 elements • Development of Logical Data Model • Tools: Data Alignment Policy Questions
  • 9. CEDS v2 Stakeholders (1 of 2) • State Agencies o State Education Agencies o State Higher Education Agencies o Social Services Agencies • Local Education Agencies o K12 o Head Start o Social Services • Institutions of Higher Education o Public o Private o Community Colleges
  • 10. CEDS v2 Stakeholders (2 of 2) • U.S. Department of Education o NCES (SLDS, IPEDS) o Financial Student Aid o EDFacts o Office of the Undersecretary o Office of Educ. Technology o Special Education • U.S. Health and Human Services • U.S. Department of Labor • Interoperability Standard Organizations • Education Associations • Foundations
  • 11.
  • 12.
  • 13. Standard Information: The Basics Element Definition Hispanic or Latino Option set Ethnicity Yes No NotSelected Domain K12 Entity K12 Student Related Use Cases
  • 14.
  • 15. CEDS Logical Data Model • Provides a high-level framework for translating standards into physical models • System-agnostic representation • 2 distinct views: • Domain Entity Schema • Normalized Data Schema
  • 17. CEDS Align •Web-based tool that allows users to: • Import or input their data dictionaries • Align their data to CEDS • Compare themselves with others • Analyze their data in relation to various other CEDS-aligned efforts
  • 18. CEDS Connect (Upcoming) Builds on the CEDS Align tool and allows stakeholders to: • Generate specific and relevant maps to a growing pool of CEDS connections
  • 19. Version 3 Content Areas • Early Learning • K12 • Postsecondary • Workforce • Career and Technical Education • Adult Education • Race to the Top Assessments
  • 20. K12 Development Work • Teaching and Learning – Formative Assessments • Supporting Teaching and Learning Initiatives • Portable Student Records • RTTA Consortia Support
  • 21. Unpacking the model What data elements and structures need to be added to What process CEDS? measures should Formative become CEDS Assessment elements? Formative Feedback What additional measured output data elements - error Instructional measureddescribe learning + Decisions Related content Learner reference progressions, etc.? metadata to Learner Standards Adjusted: Competencies include, or not Learning Progressions Instruction, (less variable) Current Learning Goals (for CEDS v3)? Criteria for Success Activities, Curriculum, Unit & Lesson Plans Practice Activities, Resources (variable inputs)
  • 22. Race to the Top Assessments • Assessment Interoperability Framework (AIF) • Identify Changes to Existing CEDS/Develop CEDS Assessment Data Elements • Beyond Data Elements and Data Model • AIF Best Practice Guidance • Prototype Demonstration • Integrate into CEDS, including updated data model and tools
  • 23. Race to the Top Assessments

Editor's Notes

  1. [K12-Postsecondary version]The high school may be trying to communicate information about a student to a university out of state. Even the most basic information about a student can be misunderstood without a common vocabulary (or standard).
  2. So what is CEDS? CEDS is a national collaborative effort to develop a voluntary, common vocabulary. <click> It provides standards for a key set of education data elements: names, definitions, option sets, technical specifications, and more. <click> Simply put, it is a Voluntary Common Vocabulary for education data. <click>
  3. Why do we need this common vocabulary? We all know educator and policymakers need accurate, timely and consistent information to inform decisionmaking. <click> We also need to share and compare these data across our P-20 sectors.While many data standards have been used in the field for decades, there has not emerged a universal language that can serve basic information needs across all sites, levels, and sectors throughout the P-20 environment. By identifying, compiling, and building consensus around the basic, commonly used elements across P-20, CEDS meets this critical need. 
  4. There are misconceptions that pop up on any project of this size so let’s be clear on what CEDS is not --Required – CEDS is a voluntary vocabulary-All or nothing – there are many different use cases that CEDS covers and not all elements have to be utilized to find benefits-A data collection – this tends to be our biggest misconception, that CEDS is a giant federal data collect, I assure you, it is not-An implementation – there is no one implementation that will work for every user. CEDS will not provide physical implementations. We will leave that up to those in the field and assume we will see many different implementations form.-Solely an ED undertaking – NCES is developing these standards with a group of stakeholders and with several public review cycles (more on our stakeholders is coming)-A federal unit record system – I know I already explained CEDS is not a data collection. We have found it doesn’t hurt to repeat that this is not a student-record system, collection, or anything like that.
  5. This is a very high level look at some of the major steps in our process. We got some important folks together, looked at the work already done, made sure we mapped up with the field, made our ideas public, modeled the elements to see if they worked telling our story, put our information in tool and then released. (This is a transition to next slides summarizing stakeholder groups.)
  6. We are very pleased by the breadth and depth of the folks we have working on this project with us. We have folks representing the entire P-20 spectrum on our stakeholder group. What is interesting is the different representation we have even within SEAs, LEAs, and IHEs. [Read list…]
  7. Note – federal staff from outside USED
  8. This is a view of the CEDS website’s home page, ceds.ed.gov, from which you can access the CEDS elements, models, tools, and more.
  9. CEDS can now be viewed and interacted with in three key ways: -By element: Via the CEDS Elements page, users can access a searchable glossary of the CEDS "vocabulary," including names, definitions, option sets, technical specifications, use cases, and more. -By relationship: Through the CEDS Data Model, users can explore the relationships that exist among entities and elements—viewable both through a Domain Entity Schema and a Normalized Data Schema. -By comparison: Supplemental tools, including the CEDS Alignment Tool enable users to take the next step and put CEDS into practice.
  10. In CEDS, a standard is comprised of several pieces of information that provide context for and describe the data items:Elements, including name and definitionOption sets, including name and definitionRelated entitiesRelated use casesAlternative names and other notesHere you see the component parts of a standard -- in this case, for the element “Hispanic or Latino Ethnicity.” On the right side, which is shows the Element Details as provided on the CEDS website, you can see the element name, definition, and option set are provided. In addition, the Domain and Related Entities provide context for how this particular element is commonly used in a data model or data system. In addition, CEDS provides a collection of related use cases.The left side of the slide represents the relationship graphically, with the entity Student in the center, next to the element along with the option set.
  11. What is the CEDS Data Model?  The CEDS Data Model presents logical view of the standards, its a system-agnostic representation that contains attributes, shows cardinality, and uses the commonly-used names for all entities. When planning to build or modify a database or implementation to align with CEDS, the Data Model provides a high-level framework to translate common entities, elements and relationships into physical models for a specific database platform that addresses the indexing, performance optimization, and normalization or denormalization appropriate for the specific application addressing local information needs.
  12. The ERD, along with XML Schema, is another one of the ways the data model is being expressed. <click> It provides a “snapshot” or “picture” of what the data model looks like. Users can navigate between the entities, or major “buckets,” and readily identify their relationships with other components within the data model.
  13. We do most of our work in three main sub-groups: early learning, K12 and postsecondary. This year we will also be expanding into workforce, CTE, adult education, and race to the top assessments.
  14. Let me highlight some of the K12 work going on.1. Teaching and Learning - Formative AssessmentsBuilding on the work of othersProviding context2. Supporting Teaching and Learning InitiativesCCSS IdentifiersLRMISLC/SLI3. Portable Student Records – supportinginteroperabilty work for our mobile student population.
  15. Here is a quick view of how we are approaching formative assessments. This work is being done directly with our school district stakeholders. We are looking at different parts of this process and what elements are needed to support each one.
  16. Finally, we have just started some work to support the Race to the Top Assessments…
  17. Finally, we have just started some work to support the Race to the Top Assessments…