Jessa ValentineCenter on Wisconsin Strategy (COWS)
WPFP ConferenceJune 30, 2010
Adult Education Transitions in Wisconsin:
Fixing the Leaky Pipeline
Staying Out of the Weeds
Continually steer analysis towards policy and practice questions you want answered
Think about the story you want to tell and the most effective, politically possible approach to reporting data
Keep an eye to institutionalization
Why A Pipeline Analysis?
Policy agenda: Better understand and improve key adult transitions (between adult education/postsecondary, between postsecondary/workforce)
Provide a baseline for thinking about ways to improve policy and practice
Evaluate effectiveness of career pathways and bridge programs
Help persuade policy makers of need for increased investments
RISE Initiative
Shifting Gears, Joyce Foundation
Co-leads: Wisconsin Technical College System and Wisconsin Department of Workforce Development
Increase the number of adults who earn postsecondary credentials related to high-demand occupations
Strategy: Career Pathways and Bridges
RISE Strategic Focus Areas
DataFoundational data“Pipeline Analysis” inspired by
WA work and assisted by CCRC (Davis Jenkins)
Stakeholder Engagement
Policy Change
Wisconsin RISE Target Population
Adults 25-54 without 2- or 4-yr college credential or not proficient in English
1.4 million
Who worked last year 1.3 million
Who made less than WI median wage ($15.11)
695,000
Source: American Community Survey, 2007
Why Focus on Adult Transitions?
Educational Attainment of Adults Ages
25-54 by Race and Ethnicity, Wisconsin, 2008
White Black LatinoNo high school diploma or equivalent 5% 19% 38%High school diploma/GED only 31% 34% 28%Some post secondary education (no degree) 23% 26% 18%Asssociate degree or higher 41% 22% 16%
Source: Working Poor Families Project, ACS 2008
Differences with Existing Analysis
Focus on older adults (25+)Measure progress irrespective of goalsFocus on completion and long-term
outcomesLink
inputs (enrollments, credits)outputs (completions)outcomes (employment, earnings, further
education)Identify key transition points meaningful to
student success – momentum points
Preliminary Data Set
Population: Students who wereFirst-time in WTCS in FY 200025+ years of ageNo prior postsecondary education
Student groupsESL, ABE, Developmental/Remedial,
Postsecondary
Observation window: 2000-2008
Student Progress Data(Sources for Momentum Points)
# of ABE and ELL credits# of Developmental/Remedial credits# of Postsecondary creditsEnrollment in a postsecondary programCompletion of a postsecondary programCompletion of 12 or more postsecondary
credits
Students Who Eventually Enroll In A Postsecondary Program
Who Are White ABEDev/Rem
Postsec
% of all students 64.9 88.5 83.9
% of students who enroll in program
71.4 89.1 83.7
Students Who Eventually Enroll In A Postsecondary Program
Who Have HS Diploma or Equivalent
ABEDev/Rem
Postsec
% of all students 51.3 87.2 92.6
% of students who enroll in program
77.5 94.0 93.2
Credits Taken
ESL ABE Dev/Rem Postsec
100%
(2,615)100%
(9,237)100%
(1,223)100%
(10,988)
1 to less than 3 ESL 42.3
More than 6 ESL 35.1
1 to less than 3 ABE 12.5 57.7
More than 6 ABE 8.9 17.8
1 to less than 3 D/R 1.4 7.5 77.0
More than 6 Dev/Rem 0.7 1.9 4.2
3 or more PS 6.8 29.1 56.5 82.4
Enrolled postsec program
3.8 23.4 52.8 45.2
Ever Enrolled in Program
ABE Dev/Rem Postsec
100 (2,158) 100 (645) 100 (4,972)
Took 3 or more college credits 96.6 96.0 97.3
Completed 12 or more college credits 80.6 83.7 62.5
Completed apprenticeship or short-term program
13.8 13.8 25.5
Obtained technical diploma 10.2 12.6 6.8
Obtained applied AD 21.6 27.1 14.3
Obtained any PS credential 45.9 53.7 46.9
ABE Students100
23.4
10.7
0
20
40
60
80
100
Total Enrolled in a program Completed apprenticeship or short-term voc program, 1 or 2 year technical diploma, or
Associate Degree
Perc
ent
89%: no diploma or degree
Developmental/ Remedial Students
100
52.8
28.4
0
20
40
60
80
100
Total Enrolled in a program Completed apprenticeship or short-term voc program, 1 or 2 year technical diploma, or
Associate Degree
Perc
ent
72%: no diploma or degree
Post-Secondary Students
100
45.2
21.2
0
20
40
60
80
100
Total Enrolled in a program Completed apprenticeship or short-term voc program, 1 or 2 year technical diploma, or
Associate Degree
Perc
ent
79%: no diploma or degree
Current Data Analysis
District-level analysis and comparison to state
18-24 year olds includedFull-time versus part-time student statusAdditional momentum points (e.g.,
college level “gatekeeper” math and English)
Next (Ongoing) Steps‘Roll out’ new data and gain buy-in from key groups:
state and district level
Incorporate selected measures into existing performance measurement systems
Connect to wage data from UI
Link to WIA to track these participants’ education outcomes
Codify Bridges and Pathway ‘chunks’ to track them in future data analysis
Key Lessons
Maintain focus on policy questions of interest (low-income working adults, transitions, outcomes)
Consider existing relationships and best approach for accessing data (trusted outsider, trusted insider, politically-powerful outsider)
Be mindful of appropriate internal versus external products, and develop compelling story line for each
Key Lessons
While you build it, work with what you haveIf you build it, they won’t necessarily come
(Even the best data system and the best data analysis is useless without stakeholder engagement and buy-in)
Cultivate an internal championHave an exit strategy!—focus on replicable
process
RISE: Pathways through EducationM A Y / J U N E 2 0 1 0
Upcoming Data Pipeline Study Release“The Shifting Gears program places an important
emphasis on using data to improve educational attainment for low-skill adult learners. To this end, the WTCS and UW-COWS have been working to build a ‘pipeline’ data system that improves our ability to track the educational trajectory of low-skill adults through technical college education. This work will lead to a better understanding of how successfully technical college students navigate key educational transitions that lead to successful outcomes. Results of the pipeline analysis will be widely shared with technical college audiences this summer.”
Data Makes People Uncomfortable
Data Makes People Pay Attention