Santiago Cueto, Young Lives Director in Peru presented at CIES, Mexico City 25-28 March 2018 on findings from the Young Lives school surveys.

1. Inequalities in educational opportunities
and outcomes in secondary schools in Peru
Santiago Cueto,
in collaboration with Gabriela Guerrero, Juan Leon and Claudia Felipe
GRADE

2. Background: YL´s Primary School Survey (2011)
• Data were collected in 132 schools, representing four
types of schools: private urban, public urban (Spanish),
and public rural (Spanish and bilingual) schools.
• Several studies using the above and others from Young
Lives show that children who are poor, rural, with
mothers with only a few years of education, or
indigenous have lower results in all outcomes but also
poorer educational opportunities (Guerrero et al, 2012).

3. Opportunities and outcomes are linked to
student and family backgrounds
Individual and
family
characteristics
Educational
results of
students
Educational
opportunities

4. Purpose of the secondary school survey
To analyze the extent of inequality of opportunities and
outcomes among secondary schoolchildren in Peru and
the extent to which these are associated.
The sample includes Young Lives children and their
in the last three years of secondary school.

5. Methods
• School principal's Questionnaire
• Mathematics and Communication teacher questionnaire
• Student questionnaire (3rd, 4th and 5th year of high
school)
• Achievement test in Mathematics
• Achievement test in Reading Comprehension
• School infrastructure and other characteristics
• Data collected in June to August 2017

6. Sample characteristics (n and average
age)
Rural Urban National Average age
(years)School year Public Public Private Public Private
Third
13 54 8 67 8 15.0
[119] [873] [141] [992] [141] [14.4]
Fourth
19 210 44 229 44 15.1
[80] [2979] [796] [3059] [796] [15.1]
Fifth
10 106 51 116 51 15.6
[37] [1874] [902] [1911] [902] [16.0]
Note: Number of YL children is without parentheses.
Number of peers is in brackets.
• 515 children of the younger cohort (average age 15.2 years), and
• 7801 peers in 185 schools
• From 9 regions, randomly selected

7. Analyses
For the descriptive analyses, we classified schools by
terciles based on the average wealth index of the students
attending this school.
The wealth index is formed by the following variables:
- Housing quality, that considers the material of the floors,
ceilings, walls and number of persons per room.
- Durable consumer goods that considers possession of
some fixed assets.
- Basic services at home considers access to electricity,
piped water, and source of energy, among others.

8. Number and type of schools and annual learning
time by tercile
Bottom tercile Middle tercile Top tercile
Public rural 10 0 0
Public urban 48 47 15
Private urban 6 17 49
Total schools 64 64 64
Source: Young Lives School Survey – Peru
Schools by tercile
Bottom tercile Middle tercile Top tercile
Effective learning hours until May 31,
2017
330.57 313.32 367.77
Daily schedule 6.11 5.98 6.58
Learning time by school terciles
Source: Young Lives School Survey – Peru

9. Children’s characteristics
Students characteristics by school terciles
Bottom tercile Middle tercile Top tercile
Wealth index 0.69 0.81 0.85
Male (%) 42.51 52.38 51.66
N of persons per room at home 1.74 1.66 1.53
Children who report they work (%) 29.65 14.74 10.47
Indigenous (%) 18.07 6.31 2.27
Maternal education (%)
Secondary incomplete or less 70.64 39.00 17.46
Secondary complete or more 29.36 61.00 82.54
Source: Young Lives School Survey – Peru
The Wealth index is a composite score comprised by measures of housing quality, access to services, and consumer
durables

10. Resources at school
Bottom tercile Middle tercile Top tercile
Psychologists 45.00 55.81 94.44
Nurses 0.00 9.52 16.67
Teacher in charge of the computer room 48.78 71.43 84.91
Librarians 46.34 52.38 28.30
Administrative staff 85.71 97.62 100.00
Classrooms in poor condition (%) 37.50 21.88 9.52
Source: Young Lives School Survey - Peru

11. Teachers’ characteristics
Teacher's characteristics
Bottom tercile Middle tercile Top tercile
Graduate studies (%) * 32.43 39.30 28.74
Studied to be a teacher (%) 93.05 97.28 86.23
Years of experience as a teacher 17.12 19.51 14.34
Contract teacher (%) 41.31 36.19 80.24
Missed school in the last 30 days (%) 13.90 22.96 20.36
Received training (%) 79.15 71.98 64.07
Only public schools
In Teacher's Professional career (%) 62.75 70.23 74.36
Received pedagogical support (%) 56.28 67.44 43.59
Source: Young Lives School Survey – Peru
*Master’s degree or doctorate

12. Principals´leadership
Principal's work meetings with teachers and leadership
Bottom tercile Middle tercile Top tercile
Principal's work meetings with teachers (%) 96.91 91.05 94.61
How often do these meetings occur?
Once a month or more (%) 65.70 35.00 69.00
Every two months or less (%) 34.30 65.00 31.00
Principal’s leadership* 12.16 12.05 12.56
Source: Young Lives School Survey – Peru
* Index values from 0 to 14

13. Academic self-concept and self esteem
Academic self-concept and self esteem*
Bottom tercile Middle tercile Top tercile
Self esteem 498.15 501.16 500.69
Academic self-concept
Reading 502.10 499.78 497.32
Mathematics 490.96 502.37 509.04
*Standardized index. Mean:500, standard deviation:100.
For self-esteem and reading the differences are not statistically significant
For mathematics all differences are significant
Source: Young Lives School Survey - Peru

14. Math scores by terciles
433.5
467.4 472.3
482.5 511.5 516.6
477.0
526.0
573.7
300.0
350.0
400.0
450.0
500.0
550.0
600.0
Third year Fourth year Fifth year
Math score by terciles
Bottom tercile Middle tercile Top tercile
Slope in top tercile = 47.808
Slope in middle tercile = 20.568
Slope in bottom tercile = 18.608

15. Reading scores by terciles
438.4
471.4
486.8
467.6
507.2 516.6489.8
525.4
559.4
300.0
350.0
400.0
450.0
500.0
550.0
600.0
Third year Fourth year Fifth year
Reading score by terciles
Bottom tercile Middle tercile Top tercile
Slope in top tercile = 43.037
Slope in middle tercile = 17.928
Slope in bottom tercile = 27.183

16. Determinants of mathematics and reading
achievement (1)
Mathematics Reading
Male 0.10*** -0.05**
Mother's education: Secondary incomplete or less
Secondary complete or more 0.10*** 0.14***
N of persons per room at home -0.02+ 0.01
Wealth index 0.03+ 0.02
Besides studying, he/she works outside his home -0.06*** -0.06***
Year grade: base 3rd year
4th year 0.14*** 0.12***
5th year 0.20*** 0.18***
Self-concept of the student in mathematics/reading 0.26*** 0.14***
School's area: Urban 0.01 0.06*
School wealth index: bottom tercile
Middle tercile 0.15*** 0.13***
Top tercile 0.12** 0.10**
Standardized coefficients
*** p<0.001, ** p<0.01, * p<0.05, + p<0.1

17. Determinants of mathematics and reading
achievement (2)
Mathematics Reading
Public school -0.12** -0.07*
School has internet 0.05+ 0.05+
Days of class * hours per day until 31 may 2017 0.06+ 0.03
Leadership of the principal 0.05* 0.11***
Years of experience as a teacher 0.07 0.09
Years of experience as a teacher squared 0.02 -0.12
Teacher has missed class in the last 30 days 0.02 0.04
Studied to be a teacher -0.08* -
Teacher completed graduate studies 0.02 0.04+
Observations 7,167 7,049
R-squared 0.3 0.2
F test 29.88 40.20
Standardized coefficients
*** p<0.001, ** p<0.01, * p<0.05, + p<0.1

18. Findings and next steps
• Socioeconomic variables of children explain a lot of
the results. Among the school variables, the role of
the principal seems relevant for explaining
achievement.
• Next steps: Explore differences by type of school
(public versus private)
• Take advantage of the available longitudinal data of
YL´s children to assess the relationship between the
wealth index in round one and their educational
opportunities and performance in secondary.

19. www.ninosdelmilenio.org
(for Peru, in Spanish)
www.younglives.org.uk
(for India, Ethiopia, Vietnam and Peru, in English)
NinosDelMilenio.org @NinosDelMilenio
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