This presentation from the OECD Disrupted Futures 2023: International lessons on how schools can best equip students for their working lives conference looks at Challenging inequalities “Matching High School Endorsement and Major Program of Study Choices for Texas College Students”. Presented by Maria Adamuti-Trache and Yi Leaf Zhang. Discover the videos and other sessions from the OECD Disrupted Futures 2023 conference at https://www.oecd.org/education/career-readiness/conferences-webinars/disrupted-futures-2023.htm Find out more about our work on Career Readiness https://www.oecd.org/education/career-readiness/

1. MATCHING HIGH SCHOOL
ENDORSEMENTAND MAJOR
PROGRAM OF STUDYCHOICES
FOR TEXASCOLLEGESTUDENTS
Maria Adamuti-Trache
Yi Leaf Zhang
University of Texas at Arlington
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2. Background
◦ Adolescent Career Aspirations
◦ Do high school students know what they would like to do when they “grow up”?
◦ Although career goals are expected to change over one’s life course, research shows that early career
aspirations help students plan their education accordingly (Beal & Crockett, 2010; Gottfredson, 2002; Nota
et al., 2015; Saw et al., 2018)
◦ Increasing awareness of post-high-school pathways is a key strategy to developing an educated workforce
that meet local and national economic demands.
◦ College and Career Readiness (CCR)
◦ Are high school students ready for college and/or career?
◦ “A student who is ready for college and career can qualify for and succeed in entry-level, credit-bearing
college courses leading to a baccalaureate or certificate, or career pathway-oriented training programs
without the need for remedial or developmental coursework” (Conley, 2012, p.1)
◦ Strategies and interventions to better engage youth in constructing their future careers.
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3. Texas Context
◦ Current Texas Policies
◦ Closing the Gap by 2015 followed by the 60x30TX strategic plan
◦ 60% of young adults (25-34) will complete some PSE credentials by 2030 (THECB, 2015).
◦ College and Career Readiness
◦ In 2006, the 79th Texas Legislature passed HB1, asking Texas Education Agency (TEA) and Texas Higher
Education Coordinating Board (THECB) to develop standards to address what students must know and be
able to do to succeed in entry-level courses at post secondary institutions in Texas  Changes in the
standardized testing (STAAR – State of Texas Assessment of Academic Readiness)
◦ Career Aspirations  TX Adopted a New High School Graduation Program in 2014/15
◦ Grade 9 students choose one of five endorsement pathways for high school graduation
◦ Endorsements thus seem to be equalizing the pathways a student may take, combining the rigor needed to
be successful in college and the application needed for today’s job market.
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4. 4

5. Purpose of Study
◦ This study will focus on the 2014-15 Grade 9 cohort who enrolled in Texas
postsecondary institutions in the Fall of 2018 immediately after high school
graduation.
◦ First, the study will compare endorsement completion by socio-demographic factors
(i.e., gender, race/ethnicity, social class) and academic preparedness to reveal the
presence of social inequalities in shaping career aspirations during secondary
education.
◦ Second, we will examine the matching between high school endorsements and major
programs of study for the college students at the intersection of socio-demographic
characteristics and academic preparedness .
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6. Data Source & Sample
◦ Texas Education Research Center (ERC) repository
◦ State Longitudinal System that includes student- and school-level data
◦ 2014/15 Cohort of 9th graders: N=419,924
◦ n =269,254 (completed at least one endorsement by Fall 2018, 64.1%)
◦ n =146,348 (students enrolled in PSE who declared major programs, 34.9%)
◦ Grade 9 student data  Socio-demographics: Gender; Race/ethnicity; Social class
(economic disadvantage indicated by free lunch eligibility)
◦ Foundation high school program Completed endorsements (STEM; BUS; PUB; ARTS;
MULTI)
◦ Grade 8 Testing Data – STAAR assessments
◦ Reading; Mathematics & end-of-course (EOC) for Algebra I  unsatisfactory, satisfactory;
advanced levels
◦ 2018 PSE enrollment & choice
◦ PSE pathway: 4-year institution; 2-year institution; Non-participant
◦ Major program of study: S&E; BUS/MAN/IND; PUB/LEG/HEALTH; SOC/EDUC;
HUM/LIBARTS
419,924
269,254
154,402
146,348
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7. Analytical Framework
◦ The study is guided by the College and Career Readiness (CCR) framework (Conley, 2010, 2012) that
highlights critical areas for post-high-school transitions that include both academic (e.g.,
achievement) and nonacademic (e.g., dispositions, behaviors) factors affecting students’ readiness
for college and careers.
◦ Texas STAAR tests that measure students' mastery of content knowledge in core subjects, and their analytical
and critical thinking skills  academic factors
◦ Endorsement completion as a proxy for career aspirations  academic & nonacademic factors
◦ The study employs descriptive statistics and multivariate analyses to examine the matching of career
aspirations (i.e., endorsements) and major program choices, at the transition from high school to
college, and whether this transition is marked by an equitable access to educational opportunity for
all Texas students.
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8. High School Endorsement Choices by Demographics
8
52.2 51.8
60.4
29.0
39.1
48.2
47.8 48.2
39.6
71.0
61.0
51.8
0.0
20.0
40.0
60.0
80.0
100.0
ALL STEM BUS PUB ARTS MULTI
Gender
Male Female
55.3
36.0
51.8 58.1
43.8 46.1
44.7
64.0
48.2 41.9
56.2 53.9
0.0
20.0
40.0
60.0
80.0
100.0
ALL STEM BUS PUB ARTS MULTI
Social Class
EconDisadv EconAdv
29.5 38.3 35.2
23.4
34.5 33.7
3.8
10.6
2.6
4.5
6.9 5.6
13.0
7.5
10.6
11.5
8.2 11.2
51.5
41.2 49.8
58.9
48.3 47.4
0.4 0.3 0.4 0.3 0.3 0.3
1.7 2.1 1.5 1.5 1.9 1.9
0.0
20.0
40.0
60.0
80.0
100.0
ALL STEM BUS PUB ARTS MULTI
Race/Ethnicity
White Asian/Pacific Black Hispanics Indigenous Mutiracial
 By 2018, about two thirds of students completed at least one
endorsement  successfully explored possible careers.
 Choice of endorsements associated with socio-demographics
 Female students more likely to choose Public Service
and Arts endorsements
 Economic disadvantaged students likely to choose
Public Service and Business endorsements
 Race/ethnicity: White and Asian (STEM/ Arts/ Multi);
Black and Hispanics (Business/ Public Service)

9. Endorsements & Pre-High School Academic Preparation
9
26.6
53.1 50.5
36.0
44.4
27.2
26.5 27.3
27.5
26.5
46.2
20.4 22.0
36.6
29.1
0.0
20.0
40.0
60.0
80.0
100.0
STEM BUS PUB ARTS MULTI
Reading
Level 1 Level 2 Level 3
23.4
52.4 52.4
38.0
45.0
18.1
26.2 24.3
23.6
23.7
7.1
4.0 3.6
5.9
5.0
16.1
7.9 8.5
11.0
9.6
35.3
9.8 11.2
21.6
16.8
0.0
20.0
40.0
60.0
80.0
100.0
STEM BUS PUB ARTS MULTI
Math/Algebra
Level 1 Level 2 Level 3 Level 4 Level 5
 Endorsements associated with academic preparation
 Reading: Unsatisfactory levels vary from 27% (STEM) to 53% (BUS)
 Math/Algebra: Unsatisfactory levels vary from 23% (STEM) to 52% (BUS and PUB end).
 Best prepared students aspire to STEM and ARTS careers.
 Overall, endorsement choices are academically and socially constrained and stratified.

10. Matching Endorsements & College Majors
◦ Correspondence Analysis: Multivariate technique that summarizes categorical data in two-way (stacked) tables and
provides a visual information of data distribution  row and column profiles turn into points displayed in an n-
dimensional space.
◦ Which variables contribute to explain the largest amount of profile distribution along each principal axis?
◦ “Correspondence analysis is a relational technique of data analysis whose philosophy corresponds exactly to what, in
my view, the reality of the social world is. It is a technique that ‘thinks’ in terms of relation” (Bourdieu & Wacquant,
1992, p. 96).
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College outcomes (Major
program area) (5 column
profiles)
HS career aspirations
(endorsements)
(5 row profiles)
Socio-demographics (10 row
profiles)
Readiness (achievement)
(8 row profiles)
• S&E
• BUS/MAN/IND
• PUB/LEGAL/HEALTH
• SOC/EDUC
• HUM/LIB-ARTS
• STEM
• Business & Industry (BUS)
• Public Service (PUB)
• Arts & Humanities (ARTS)
• Multidisciplinary (MULTI)
• Sex (Male/Female)
• Race/ethnicity (Asian/
Black/Hispanic/Indigenous/Mixe
d Race/White)
• Econ advantage (Yes/No)
• Reading (1-3)
• Math/Algebra (1-5)

11. CA Map
Horizontal axis: 74%
Vertical axis: 20%
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 Horizontal: People vs. Technology- oriented
Majors  Career axis (major programs)
 Horizontal: Academic Achievement & High
School Endorsement  CCR axis
 Horizontal: Socio-demographics axis
 Vertical: Gender & PUB vs BUS endorsements
The matching of endorsements & college
majors suggests how student ‘choices’ are
reproducing social inequality in education.
 Chi-square statistics: (χ2 =
40,221.5, df = 88, p < .0001) HS_STEM
HS_BUS
HS_PUB
HS_ARTS
HS_MULTI
Male
Female
White
Asian
Black
Hispanic
Indigenous
MixedRace
EconDisadv
EconAdv
RE-Lev1
RE-Lev2
RE-Lev3
MA-Lev1
MA-Lev2
MA-Lev3
MA-Lev4
MA-Lev5
S&E
BUS/MAN/IND
PUB/LEG/HEALTH
SOC/EDUC
HUM/LIBART
-0.3
-0.2
-0.1
0
0.1
0.2
0.3
-0.3 -0.2 -0.1 0 0.1 0.2 0.3 0.4 0.5

12. Matching: High School Endorsement & Major Programs (%)
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High School
College STEM BUS PUB ARTS MULTI
S&E 36.7 19.1 17.1 23.2 23.1
BUS/MAN/IND 13.2 22.8 6.5 11.3 14.3
PUB/LEG/HEALTH 15.2 15.2 32.6 16.6 18.7
SOC/EDUC 6.4 5.4 8.6 8.9 7.5
HUM/LIBART 28.6 37.6 35.2 40.0 36.3
Does the Endorsement
initiative achieve its goal?
 Matching for STEM,
BUS, PUB, ARTS
 All endorsements 
large %s in college
majors related to
Humanities/ Liberal arts
(general education?)
 MULTI  S&E (likely
Advanced curriculum)
 ARTS  S&E (likely
students taking more
than one endorsement)

13. Discussion & Conclusion
◦ Academic vs. Applied Endorsements [raising social justice concerns]
◦ Academic Oriented Endorsements STEM <-> High achievement levels  S&E majors
◦ Who: Asian, White, Male, Econ Advantaged
◦ Applied Endorsements: Business & Industry and Public Services <-> Lower achievement levels  BUS/MAN/IND &
PUB/LEG/HEALTH majors
◦ Who: Racial/ethnic minorities & Economically Disadvantaged
◦ People- vs. Technology-oriented endorsements & college majors [reinforcing gender stereotypes]
◦ People-oriented: Public Services and ARTS  PUB/LEG/HEALTH and SOC/EDUC and HUM/LIBARTS (female)
◦ Technology-oriented: Business & Industry and STEM  S&E and BUS/MAN/IND (male)
◦ Career Pathway Gaps [indicating the presence of multiple sources of inequality]
◦ Academic vs. Applied pathways; Race/ethnicity; Social class.
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14. Q&A
Contact Information
Dr. Maria Adamuti-Trache mtrache@uta.edu
Dr. Leaf Zhang
Lyzhang@uta.edu
Department of Educational Leadership & Policy
Studies
The University of Texas at Arlington
Arlington, TX 76013
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