1. Indigenous students’ performance and school effects in Guatemala and Peru
Esteban Villalobos, Diego Portales University
Ernesto Treviño, Diego Portales University
Andrea Alvarado, Columbia University

2. Context
Peru and Guatemala both have significant proportions of indigenous population: 41.0% in Guatemala and15.7% in Peru
Guatemala has a larger share of population living in rural areas than Peru
Cultural linguistic aspects: 23 Mayan languages in Guatemala v/s 13 linguistic families from 51 ethnic groups in Peru (based on Census data)
Quantitative measurements and cultural complexities: difficult, but necessary and useful.

3. More Context
International evidence: indigenous children have lover achievement than non-indigenous
Indigenous families have lower educational levels, lower service accessibility
Both countries have included recognition of indigenous languages and introduced intercultural bilingual strategies in schools.

4. How can we describe and explain the educational achievement gap that exists between indigenous and non-indigenous students in Peru and Guatemala (and in Latin America)?

5. Research Background, two approaches: Oaxaca Decomposition and Propensity Score Matching
Oaxaca Decomposition: assessing the impact of students characteristics, school characteristics, and the interaction amongst them, on the educational outcomes in language (Spanish) and mathematics. This study covered 4 countries of the SERCE dataset for third and sixth grade (Colombia, Ecuador, Guatemala & Peru).
Research Findings:
40% of the gap was explained by differences in children and school characteristics.
In this study we identified that both populations were too different from each other, thus we needed to reduce the selection bias.

6. Research Background, two approaches: Oaxaca Decomposition and Propensity Score Matching
Propensity Score Matching: attempt of reducing the selection bias, in order to make these populations comparable. Modeling “the probability of being indigenous”, we tested family and school level variables in 4 countries (Colombia, Ecuador, Peru and Guatemala), separating them by urban/rural condition.
Research findings:
Family level:
School level:
o Indigenous: strong negative effect
o Effect of climate & infrastructure in third grade
o SES of children: strong positive effect
o Mothers education: not clear effect
o Organization of the classroom & Infrastructure school in sixth grade
o Preschool also varied
Teachers speaking the indigenous language had unclear effects: sometimes this variable had significant effects, some others it did not
o Urban/Rural: Varied in certain contexts, not in others

7. What did we learn from these analyses?
Language scores are much more affected by the conditions of origin of children than math scores. This is probably related to the fact that the language is learned by children in their homes in an unstructured way before it is taught to them in school.
On the contrary, math provides a more homogeneous setting for children, since it is mainly learned at school through formal and systematic teaching.
Limitations of the PSM:
Although it is a sophisticated technique that allowed for an appropriate reduction of the selection bias, it left us with too few cases, which affected particularly our indigenous subsample (the focus of our analysis).
In addition, the question remains in terms of whether the indigenous students have lower scores due to their disadvantaged background, or due to the fact that they are overrepresented in poor-quality schools

8. Multilevel Analysis New dimensions/variables were introduced:
SES of the classroom (originally only considered for family level)
Size of the class (average number of children in the classroom)
Also included a broader version of the school administration:
Private v/s public
Urban v/s rural
The variable for teachers who speak indigenous language was recoded in order to reflect the proportion of students in each classroom that observed this characteristic; in this way, the former individual-level variable was transformed into a classroom-level variable.

9. Data & Methods
Dependent variables: Educational achievements of the students of third and sixth grades expressed as test scores for language and math
Predictors at student/ family level:
Student is indigenous (speaks indigenous language at home)
Socioeconomic level of the family
Student repeated one or more years in school
Student attended preschool
Education level of the mother
Sex of the student
Predictors at the school level:
Climate of the class index (3 grade)
Organization of the classroom index (6 grade)
Infrastructure of the school index
Administration of the school (urban public, urban private, rural)
Average n° of students per class
Average SES of the class
Teacher speaks indigenous lang.
Number of classrooms per grade in the school
Interaction term of indigenous condition (student level) and SES (classroom level)

10. Results and analysis: Third grade
Random intercept and analysis of variance
Both countries present a significant variation of both math and language scores among schools. This variation decreases significantly when introducing school-level predictors in the model.
Also, in both countries there is an important variation of scores among students within schools, although its reduction due to the inclusion of family-level predictors is much smaller than in the first case.

11. Differences by Country
Results and analysis: Third grade
Differences by Test
Differences by Country
Gender gap in math: lower scores for female students
Impact of the school infrastructure affects language scores in both countries
Education of the mother only affects math scores
In most of the factors associated with the socioeconomic structure of the country, the coefficients for Peru indicate a greater impact on test scores than those for Guatemala.

12. Results and analysis: Third grade
Commonalities
School-level:
Better classroom climate increases scores in both tests and countries
Higher average SES of classrooms have a strong positive effect on test scores
Family-level:
Positive effect of (an increase in) SES of the family
Negative impact of having repeated a year

13. Results and analysis: Third grade
The impact of speaking an indigenous language is greater in Peru than in Guatemala, and it is also greater for language scores than for math scores (which is consistent with the findings from former analyses).
In any case, indigenous-language-speaker students have lower test scores than not indigenous-language-speakers, net of their familial background and the characteristics of their schools.

14. Results and analysis: Sixth grade
The variance among schools, and the variance among students within schools, behave very similarly to scores in third grade: great reduction of school-level variation when introducing predictors, minimal reduction of individual-level variation.
Classroom SES becomes even more relevant in explaining test scores in sixth grade (cumulative effect?)

15. Results and analysis: Sixth grade
Some of the effects become stronger:
Having repeated a year has a greater negative impact
The gender gap in math becomes wider; in Guatemala, the gap becomes significant for language scores
Disorganization of the classroom affects negatively both tests, although it is more relevant in Guatemala

16. Results and analysis: Sixth grade
Teacher speaks indigenous language
An increase in this predictor is only significant in Guatemala, and it has a negative effect on test scores – especially in math scores
The interaction of indigenous language (family level) and classroom SES (school level) has unclear, mixed effects in different grades, tests and countries

17. Conclusions
The impact of school-level predictors in explaining the variation of test scores suggests that schools are a critical field in the battle against inequality. Some of the main areas to consider are the classroom climate, organization, and socioeconomic composition.
The most important factor in all levels of this analysis is the classroom SES; this finding puts an accent on the school segregation debate.
Inequalities tend to settle from third to sixth grade. In particular, the impact of speaking an indigenous language increases.

18. Final thoughts and further hypotheses
The systematic incorporation of Intercultural Bilingual Education (IBE) strategies should be considered in order to reduce origin inequities; this is an ongoing process in both Peru and Guatemala.
It is important for these strategies to be incorporated in the different levels and processes of the educational system: policy design, managing and, more importantly, at schools and classroom levels. This requires the involvement of stakeholders at all levels.
Additionally, those strategies need to incorporate socioeconomic desegregation processes in order to increase a positive peer effect and reduce origin inequities.

19. Thank you! eavillalobos@uc.cl aa3340@columbia.edu