1 / 19

Advances in Longitudinal Data and Data Use

Advances in Longitudinal Data and Data Use. Education Research & Data Center Spring 2014 Conference Carol Jenner, ERDC. Preview. ERDC data Timing “Thinking P-20” Suggestions for requestors. What do we have?. Early learning: Early Childhood Education and Assistance Program (ECEAP)

veta
Download Presentation

Advances in Longitudinal Data and Data Use

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Advances in Longitudinal Data and Data Use Education Research & Data Center Spring 2014 Conference Carol Jenner, ERDC

  2. Preview • ERDC data • Timing • “Thinking P-20” • Suggestions for requestors

  3. What do we have? • Early learning: Early Childhood Education and Assistance Program (ECEAP) • Washington public primary/secondary/postsecondary • National postsecondary • Apprenticeship • Washington employment/unemployment • Additional employment for specific uses (out-of-state, federal, military) • K-12 staff, early learning staff P20W Data

  4. How far back? P20W Data

  5. How do we link? • Approximately 6 million unique education-sector name-birthdate-student identifier combinations grouped by ERDC-assigned “P20 ID” • Links improve as individual is represented in increasing number of sectors • For example: • James King* born 12-1-1991 attends school 1 • Buddy King* born 12-1-1991 attends school 2 the next year • Not enough information to relate the two • Then James “Buddy” King* born 12-1-1991 enrolls in a CTC *These are invented names, used for illustrative purposes. P20W Data

  6. Timing and Availability • Collection and preparation by originating agency • Usually after the end of a term, year, calendar quarter • Followed by collection and processing (including identity resolution) by ERDC • Unemployment Insurance (UI) Wage example: Timing

  7. Dual-credit timing puzzles • Running Start – student enrolled in a college class and receives both high school and college credit (if successful) • Tech Prep – student enrolled in a high school class and receives both high school and college credit if he/she receives a ‘B’ grade or above • College in the High School – student enrolls in a high school course and receives both high school and college credit (if successful) Timing

  8. Running Start • Student enrolls in Running Start class • At the end of the college term, grade is recorded at the college • Transcript information is provided to high school registrar • Running Start credit is recorded at various times in the high school transcript record – often not in spring high school record even if course was a spring term course Credits do show up in K-12 transcript files by graduation Timing

  9. Tech Prep Dual Credit • Student enrolls in high school Tech Prep class AND must register or be registered in the CTC SERS* system near the beginning of the high school term to be eligible for college credit • At the end of the high school term, high school grade is entered in SERS system • College credit recorded via “direct transcript,” typically lagged by one college term Effect: many Tech Prep credits appear in the CTC transcript in the academic year following high school course completion SERS=Student Enrollment Reporting System, which thankfully contains an articulation file that relates high school class to college course. Timing

  10. Thinking P20 • Longitudinal, cohort-based analyses • Cohort member characteristics from a single source and point in time • Cohort is followed over time as opposed to a series of snapshots • Prior characteristics can be incorporated • Cumulative • Can address educational attainment of a cohort • Ready data allows for richer analysis Thinking P20W

  11. Enables Cohort Definition • Applications Match Study – Enrollment outcomes for undergraduate applicants to public baccalaureate institutions “Applications Match Study, Fall 2010,” ERDC, August 2013. <www.erdc.wa.gov/briefs/pdf/201302.pdf> Thinking P20W

  12. A Cumulative Look • Educational attainment of 2005-06 high school graduates through 2011-12 “Washington’s Postsecondary Education Pipeline: Six-Year Outcomes for Public High School Graduates, 2005-06,” ERDC, February 2014. <www.erdc.wa.gov/briefs/pdf/201401.pdf> Thinking P20W

  13. K-12/Employment • Median hours worked by June 2009 high school graduates who attended a Washington public higher education institution in the year immediately following high school graduation Junior Year Senior Year Post-HS “Workforce Participation: Washington State High School Graduates, 2008-09,” ERDC, April 2011. <www.erdc.wa.gov/briefs/pdf/201102.pdf> Thinking P20W

  14. Early Learning/K-12 • First look at the results of linking 2012-13 ECEAP children, their spring assessment outcomes, and Fall 2013 WaKIDS kindergarten assessment outcomes Developmental Area: Social-Emotional “Early Childhood Program Participation & WaKIDS Outcomes,” ERDC, March 2014. <www.erdc.wa.gov/briefs/pdf/201404.pdf> Thinking P20W

  15. Employment • Don’t limit questions to median earnings • Consider also: • Industry of employment • Full-time/part-time status • Working while enrolled • Number of employers • Time-spans of a year or more rather than specific quarters • Length of time to reach living wage • Adjust for inflation • Spells of unemployment Thinking P20W

  16. Postsecondary/Employment • Washington resident bachelor’s degree graduates: one year after graduation (maximum quarter wages) Median wage values for 2008 have been inflation-adjusted to 2012 dollars using the Chain-Weight Implicit Price Deflator (IPD) for Personal Consumption Expenditures. Median wages are rounded to the nearest hundred dollars. See the cited publication for complete specification for these measures, which were requested by the National Governor’s Association. “Labor Outcomes: Public Baccalaureate Institution Graduates, 2006-07 and 2010-11,” ERDC, December 2013. <www.erdc.wa.gov/briefs/pdf/201303.pdf> Thinking P20W

  17. Employment/Education • A cohort can originate in the employment sector • Employees new to the Washington workforce in a particular quarter or year • What are the prior education experiences of this cohort? (Washington education data plus National Student Clearinghouse are data sources) • How recently were they enrolled? • How recently did they complete a degree or certificate? • In what industries are they employed? Thinking P20W

  18. Suggestions for Requestors • Think P20! • Off-the-shelf and traditional approaches can answer basic questions but longitudinal and cumulative data can enhance the effort • Remember the timing of data receipt and the effort involved in cross-sector linking. • Do not require a report “before its time” • Feel free to consult with ERDC folks when preparing a request for data or analysis Suggestions

  19. Thank you! www.erdc.wa.gov

More Related