This presentation from the OECD Disrupted Futures 2023: International lessons on how schools can best equip students for their working lives conference looks at Understanding impact through quantitative analysis “Career Design Under the Effect of School and Student Socioeconomic Status: A Global Interaction Analysis”. Presented by Ilker Kalender. 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. Career Design Under the Effect of
School and Student Socioeconomic Statu
A Global Interaction Analysis
Dr. Ilker Kalender
Graduate School of Education
Bilkent University, Turkey

2. Türkiye,
an OECD Member Country
 One of the founding member of OECD
 Along with 19 other countries, Türkiye signed
the Convention founding the Organisation for Economic Co-
Operation and Development on 14 December 1960, pledging
its full dedication to achieving the Organisation’s fundamental
aims.
https://www.oecd.org/turkiye/

3. Selected Indicators for Türkiye
 Population:
84.1 Million
 Youth population (people aged
less than 15):
22.6% of the population
17.6% for OECD Total

4. Selected Indicators for Türkiye

5. This Study
 Countries or economies have students with varying socioeconomic
status (SES). Low SES limits access for such students to qualified
teachers, quality schools, counselling, etc. (Willms, 2010).
 Quality career planning and development is one of the services
disadvantaged students receive less than their peers with higher SES.
 Many countries and economies assume a positive relationship
between SES and good quality education components. Career
planning and development is no exception.
 However, this positive relationship may be more complex than
assumed. A student’s and a school’s SES where the student is
enrolled may interact.
 A student with high SES in a low SES school may be affected
negatively in several ways. Or the opposite scenario may create
substantial opportunities. Thus, being at a “good” school may be a
prerequisite but not sufficient alone.
 A mismatch between two SES components may hinder opportunities
regarding career design. Thus, this interaction and its effect on career
planning and development need further study.
 This research hypothesizes that the interaction between school SES
and student SES impacts career-related services and focuses on
PISA 2018 data to understand how such interaction creates different
opportunities or disadvantages for countries and economies in the
career design of students.

6. PISA 2018
 79 countries and economies participated
 600 000 students
 Representative of about 32 million 15-year-olds in the
school

7. Socio-Economic Status (SES)
 Socio-economic status is defined as “the relative position for the family or individual
on a hierarchical social structure, based on their access to, or control over, wealth,
prestige and power” (Willms & Tramonte, 2015, as cited in Mueller & Parcel, 1981).
 Socio-economic status can be considered as a measure of students’ access to
family resources (financial capital, social capital, cultural capital and human capital)
and the social position of the student’s family/household.
 In PISA, a student’s socio-economic status is estimated by the PISA index of
economic, social and cultural status (ESCS).
 ESCS is a composite measure that combines into a single score the financial,
social, cultural and human-capital resources available to students (PISA 2018
Technical Report).
 In practice, it is derived from several variables related to students’ family
background that are then grouped into three components:
parents’ education
parents’ occupations
index summarising a number of home possessions
 ESCS scale was transformed with 0 as the value of an average OECD student and
1 the standard deviation across equally weighted OECD countries.

8. Achievement and Socio-Economic Status
 On average across OECD countries in 2018, a
one-unit increase in the PISA index of economic,
social and cultural status was associated with an
increase of 37 score points in the reading
assessment.
 On average across OECD countries in 2018,
socio-economically advantaged students scored
89 points higher in reading than socio-
economically disadvantaged students.
 In reading, 12% of the variation in student
performance within each country was associated
with socio-economic status.

9. School SES and Student SES
 The positive and strong relationship between student SES and student outcomes is
well-established in the literature (Garcia, 2015; Palardy, 2013; Perry & McConney,
2010a; Pokropek et al., 2015).
 SES composition of a school is positively related to student outcome. This relationship
is beyond students’ own SES levels (Palardy, 2008; Perry & McConney, 2010a, 2010b;
Rumberger & Palardy, 2005; Southworth, 2010; Sui-Chu & Willms, 1996).

10. Educational Career Questionnaire
 Several countries distributed the questionnaire.
 Collects information on interruptions in schooling, preparation for students’ future career,
and support with language learning .

11. Items Used from Educational Career Questionnaire
 I spoke to a <career advisor> at my school.
Yes / No
 I spoke to a <career advisor> outside of my school.
Yes / No
 How to write a <résumé> or a summary of my qualifications. Yes, at school
Selected / Not Selected

12. Analyses
 This is an exploratory study.
 Student SES was defined by an index ESCS (index of economic, social and cultural status)
 School SES was defined by averaging students’ SES within schools.
 Students were divided into 2 groups based on their responses.
 Students and schools in these two groups were further divided into four quartiles separately with respect to two SES variables.
 4x4 cross tables were created for each country to see if there are differences between student responses within each country.
 Cells not in the diagonal of cross tables were considered as they represent students who are in a different SES level than their
schools.
 Absolute sum of differences between responses were calculated between two responses for each respective cell.
COUNTRY A
YES (%) NO (%) Difference (%)
1 2 3 4 1 2 3 4 1 2 3 4
1 100 0 0 0 100 0 0 0 0 0 0
2 56 33 15 0.00 53 33 10 0 3 5 0
3 0 0 37 65 0 0 37 60 0 2 5
4 0 0 0 100 0 0 0 100 0 0 0

13. Results
I spoke to a
<career
advisor> at my
school.

14. Countries
under
3 Clusters
(15 countries)
1 (4.18%) 2 (9.95%) 3 (23.03%)
Australia Denmark Iceland
Brunei Darussalam Italy
Chinese Taipei Slovak Republic
Costa Rica
Croatia
Greece
Ireland
Panama
Spain
Thailand
United Kingdom

16. Results
I spoke to a
<career
advisor>
outside of my
school.

17. Countries
under
2 Clusters
(20 countries)
1 (4.51%) 2 (10.45%)
Albania Belgium
Brunei Darussalam Croatia
Chinese Taipei Denmark
Germany Ireland
Greece Serbia
Italy Slovenia
Korea United Kingdom
Lithuania
Morocco
Panama
Poland
Spain
Thailand

19. Results
How to write a
<résumé> or
a summary of
my
qualifications
at school.

20. Countries
under
3 Clusters
(21 countries)
1 (7.37%) 2 (3.50%) 3 (11.13%)
Albania Belgium Costa Rica
Brunei Darussalam Bulgaria Denmark
Croatia Chinese Taipei Iceland
Greece Hungary New Zealand
Hong Kong Malta
Panama Slovenia
Poland Spain
Serbia Thailand
United Kingdom

22. Implications
 School SES and student SES interaction create 5% to 6%, in average, differences in three career-
related items across countries.
 Differences go up to
23.03% (Iceland) for I spoke to a <career advisor> at my school.
13.67% (Croatia) for I spoke to a <career advisor> outside of my school.
12.56% (Iceland) for How to write a <résumé> or a summary of my qualifications. Yes, at school

23. Implications
 Differences may not seem so high.
 However, what matters is students, not the percentages.
 Percentages should be converted to real numbers.
 There are students out there who need appropriate career-related help is important.

24. Implications
 Countries grouped for 3 items used in this study do not have differences in terms of all domains
measured in PISA 2018 (reading, science, and mathematics).
 Countries’ achievement levels are similar within clusters. Thus, career-related activities still
need to be covered in school regardless of achievement level of students.