Factors related to secondary school students’ expectations of completing university studies in Argentina and ChileAbstract
This paper uses micro-data from the PISA 2022 Assessment Programme to study the factors related to secondary school students’ expectations of completing university studies in Argentina and Chile. We estimate a logistic regression model on the probability of having expectations of completing university studies in each country. The results show that, despite the differences between the two higher educational systems, factors such as gender, the socioeconomic level of the student, their parents’ education, his/her educational attainment, and the type of school attended (public or private) influence, in the same direction, youths‘ expectations regarding university studies. However, there are significant differences in the magnitude of the effects of some variables in the countries analysed. In particular, the expectations of middle and high-class students compared to those from lower class are higher in Argentina than in Chile. The results could be a consequence, on the one hand, that lower-income secondary school students in Argentina have reduced chances of graduation than lower-income secondary school students in Chile. On the other hand, despite the access and financial barriers present in Chilean higher education, the chances of graduation are greater than in Argentina. Note that while access to public higher education is open and tuition-free in Argentina, in Chile, a free tuition policy has been introduced for lower-income groups, and some private sector institutions have lower barriers to entry than the most selective group of public and private institutions.
Keywords:
Educational expectations - Higher Education - Related factors - Argentina - Chile
Resumo
Este artigo usa microdados do Programa de avaliação PISA 2022 para estudar fatores relacionados às expectativas dos estudantes do ensino médio de concluir os estudos universitários na Argentina e no Chile. Estimamos um modelo logit sobre a probabilidade de esperar concluir estudos universitários em cada país. Os resultados mostram que, apesar das diferenças entre os dois sistemas educacionais, fatores como o gênero, o nível socioeconômico do aluno, a educação dos pais, o desempenho acadêmico do aluno e o tipo de centro que ele frequenta (público ou privado) são muito importantes e influenciam as expectativas na mesma direção. Entretanto, há diferenças significativas na magnitude dos efeitos de algumas variáveis nos países analisados. Em particular, as expectativas dos estudantes de classe média e alta em relação às da classe baixa são maiores na Argentina do que no Chile. Os resultados podem ser uma consequência, por um lado, de que os estudantes do ensino secundário de baixa renda na Argentina têm chances reduzidas de se formar do que os estudantes do ensino secundário de baixa renda no Chile. Por outro lado, apesar das barreiras de acesso e financeiras presentes no ensino superior chileno, as chances de graduação são maiores do que na Argentina. Note-se que, embora o acesso ao ensino superior público seja aberto e gratuito na Argentina, no Chile foi introduzida uma política de ensino gratuito para grupos de baixa renda, e algumas instituições do setor privado têm barreiras de entrada mais baixas do que o grupo mais seletivo de instituições públicas e privadas.
Palavras-chave:
Expectativas educacionais - Educação superior - Fatores associados - Argentina - Chile
Introduction and objectives
A topic little explored in research focused on the transition between secondary and higher education in Latin America is the study of the factors that influence the expectations of completing university studies. As revealed by international research, this is a highly relevant issue for improving equity in access, retention and graduation from higher education. The international literature points out that the level of expectations among these students is a very important predictor of their levels of access, retention and graduation in higher education (Cabrera; La Nasa, 2000; Choi, 2018; Christofides et al., 2015; OECD, 2017). According to Terenzini, Cabrera and Bernal (2001), by the ninth grade most students have developed occupational and educational expectations that are strongly related to their socioeconomic status. The socioeconomic differences are expressed in persistence and graduation rates and the choice of different types of higher education institutions, all of which are unfavourable to lower-socioeconomic students compared to more advantaged groups. It is important to consider this issue when formulating policies that are key to improving equity in higher education.
This article analyses how different factors, such as the socioeconomic and educational level of the secondary student’s household, the student’s academic performance and gender, influence the expectations of completing university studies in Argentina and Chile. The cases we analysed share the presence of an unequal structure in access to and graduation from university education. In Argentina, most higher education students study in a public institution, while in Chile, most study in the private sector. There are also marked differences in access and financing policies. Argentina has an open and free admission system and Chile has a highly selective admission system in a group of public and private universities, which charge high tuition fees but offer the so-called free policy or Gratuidad for lower-income students enrolled in accredited higher education institutions. Also note that secondary school graduates in Chile have a higher average learning achievement than in Argentina, as reflected in the higher average value in the PISA test.
Within this framework, the research questions are twofold. First, what are the factors that influence the secondary student’s expectations in both countries, and second, to what extent do the weights of these factors differ in Argentina and Chile.
Given the absence of longitudinal surveys in Latin America, which follow the trajectory of the students from the secondary school level to their access and graduation from university, we use the data provided by the PISA test. To link the probability of having educational expectations with the possible determinants, we estimate a logistic regression model. The study of the factors that influence secondary school students’ expectations of completing university studies is innovative in the context of Latin America. We believe that this research can contribute to the design of public and institutional policies that improve equity in the transition from secondary school to university, paying particular attention to factors such as the socioeconomic and sociocultural levels of the students’ homes and gender issues.
In the next sections, we present a review of the literature and then we describe the higher education systems in Argentina and Chile. After that, we present the data used and the methodology chosen. We follow with the results and discussion. Finally, we present our conclusions.
Literature review
Having high educational expectations reduces the risk of early school leaving (Ou; Reynolds, 2008; Christofides et al., 2015), and increases both academic performance (Hao; Bonstead-Burns, 1998; Choi, 2018) and the probability of completing university studies (Andrew; Flashman, 2017). Given its importance, a literature has flourished that analyses factors associated with educational expectations. Choi (2018) uses logistic models to analyse them for Spain and finds a high correlation between expectations and academic performance, the socioeconomic and educational level of households, and the expectations of peers. Regarding other measures of academic performance, a useful complement for test scores is the grade repetition (Valdés Fernández, 2021).
There are also gender inequalities in youths’ expectations of continuing on to study at the higher education level. Hillman (2018) states that these gender differences in educational expectations have also been noted in the research literature and in the different gender enrolments at university. Elias Andreu and Daza Pérez (2019) find that the expectations are higher among women than in the case of men, even among students with similar social origins and academic results. Ali et al. (2022), who study the gap in educational expectations and achievement that exists between immigrant and native students in Qatar using the PISA dataset, find that female students in both groups have better academic performance and hold higher educational expectations. They also find that the gender gap is bigger among Qatari students than among immigrants. Elias Andreu and Daza Pérez (2017), who study the expectations regarding post-compulsory education in Barcelona, find significant differences between men and women, the latter ones present higher expectations, higher academic performance, and more consistency regarding their perception and their actual academic achievement.
Being a first-generation student is also another relevant dimension to contemplate when studying the expectations of high school students regarding the completion of university studies (Pascarella et al., 2004). First generation students (FGS) are those whose parents or guardians have not attained higher education. In a qualitative study of Chilean first generation students, Guzmán-Valenzuela et al. (2022) find that they encounter complex and multilevel challenges when making higher education choices, which are highly related to the different levels of aspirations, which are strongly anchored to both family and school social capital.
Another dimension analysed is the public or private nature of the secondary school. A study carried out in Barcelona reveals that the variable that identifies students from private schools was significant in explaining the choice of students regarding the post-compulsory studies to follow (Elias Andreu; Daza Pérez, 2017). The choice of the type of school is strongly influenced by the educational level of the parents. The choice of secondary school can be decisive in subsequent success in continuing university studies versus vocational or technical studies and in the degree programme to be chosen (Chesters, 2015).
The type of management of the institution and the educational level of the parents are, in turn, correlated with the income level of the family group. As Costa Ribeiro (2011) points out in the case of Brazil, parental wealth (measured by economic assets, income or occupational status) is a key factor in explaining inequalities in educational opportunities. This form of inequality is present in all educational transitions and reaches very high levels. Foster, Heaton and Haas (2004) stated that socioeconomic background was a primary factor influencing expectations of graduating from a university in Bogotá, while family structure was more influential in La Paz.
Choosing an institution and a degree programme occurs within the context of horizontal stratification in higher education. According to Triventi et al. (2020), institutions and degree programmes are ranked on a scale of prestige, reputation, quality, and sometimes the cost of teaching. The theory of social stratification formulated by Lucas (2001), called Effectively Maintained Inequality (EMI), has a temporal component to explain this horizontal stratification. According to Lucas (2017), while the chances of access to a level of education for the population as a whole are not high, a quantitative increase in their participation in that level of education will be enough for higher-income sectors to maintain their status. However, when the socioeconomic level begins to be irrelevant as a factor associated with school participation, then higher-income sectors seek to differentiate themselves by accessing higher-quality institutions and degree programmes. This theory arises as an alternative to the Maximally Maintained Inequality approach (MMI) (Raftery; Hout, 1993), which considers that social stratification in access to higher education is maintained until the level is saturated after universal access.
From the social reproduction perspective, Bourdieu and Passeron (1979) attribute the different educational decisions regarding higher education among young people and their families to the dominant habitus of each social sector. According to Bourdieu (1980), sectors are structured based on the positions of the agents in the social space according to the volume and structure of the economic, cultural, and social capitals they possess. In particular, to understand social inequality in education, cultural capital is quite important as a mechanism to reproduce the social conditions by the social sector. Cultural capital is internalized in individuals as habitus. This habitus includes schemes of perception and evaluation that agents acquire through their experiences according to their position in the social space. With respect to how this approach explains the differences among secondary school students’ aspirations, van de Werfhorst and Hofstede (2007) observed that class variations in terms of school performance (primary effect) are substantially related to cultural capital. Following Bourdieu, they measured cultural capital according to parental involvement in highbrow culture. However, they showed that Bourdieu and Passeron’s theory of reproduction could not explain future ambitions of students with equal academic performance that are conditional on choices of different social classes (secondary effect). In this case, Breen and Goldthorpe (1997) were able to provide a better approach to understanding secondary effects. Faced with Bourdieu’s cultural determinism regarding the effect of the social structure on the decision to continue university studies, Goldthorpe (2010) called attention to the fact that it is in the secondary effects where it is feasible to find a possibility of change, since the decision-making process of students and their families can modify the course determined by the social structure. Thanks to this, there is a possibility of designing policies that favour an informed decision-making process and that strengthen the capacity of individuals to choose a path to follow among the available options (Keung; Ho, 2020).
Valdés Fernández (2019) found that the secondary effects in Spain account for around half of the inequality observed in the expectation of university enrolment in 15-year-old Spanish students according to PISA. As stated by Valdés Fernández (2019), this finding stresses that public policy should pay attention not only to measures to compensate for learning deficits but also to those that focus on improving the decision- making process while in secondary school, especially among socially less advantaged secondary school students.
Argentine and Chilean Higher Education System
Argentina and Chile share soaring higher education enrolment rates, which positions them in the stage of universalization of access according to Trow’s classification (Trow, 2006). In addition, the participation of women in higher education is greater than men in both countries (Table 1).
Argentina’s higher education sector is composed of two types of institutions - universities and university institutes on the one hand, and non-university tertiary institutions, which provide teacher training and short vocational and technical degrees, on the other. A university and a university institute differ in that the latter offers an academic specialization in a single field of knowledge, for example, engineering. In 2022 around 2.7 million students studied at these university institutions, 80% of which were in the public sector and more than 1 million students were enrolled in the non-university tertiary institutions, 68.9% of which were in state-run institutions (Buenos Aires, 2024a, 2024b).
We can assume that the expectations of 15-year-old secondary school students of completing university studies are linked to the characteristics of the admission mechanisms to access the different higher education institutions, as well as their chances of completing secondary and higher education. Below, we briefly analyse these aspects in the cases of Argentina and Chile.
The main requirement for admission to a university or tertiary degree programme is a secondary school diploma. The public sector presents no other restrictions, such as exams at the end of the secondary school or entrance exams to the university or the non- university tertiary sector. In sum, Argentina’s higher education institutions, especially public ones, are open access. In addition, undergraduate programmes in the public sector are tuition free.
Chile’s higher education sector is composed of three types of institutions: universities, which offer academic and professional 5-year degrees; professional institutes, which can grant 4-year professional degrees and 2-year technical degrees; and technical training centres that offer 2-year technical degrees. In 2022, 56% of the 1.2 million Chilean higher education students were studying in the university sector and 84% of the total higher education enrolment were in the private sector (Salazar; Leihy, 2024).
The professional institutes and the technical training centres tend to have non- selective admission processes. This contrasts with what occurs in the university sector, especially in those institutions that belong to the Council of Rectors of Chilean Universities (CRUCH), which encompasses the public ones and some prestigious private universities. This group of institutions applies a centralized and selective admission system. In the admission procedure, universities consider the results achieved in the Transition Test and the secondary school grade average. The remaining private universities that do not participate in this centralized process generally take into account the results of this test and the secondary school grade average (Zapata; Tejeda, 2016).
Both public and private institutions charge tuition fees. The average tuition fees charged by higher education institutions at the undergraduate level are quite high:
$8,316.9 in PPP dollars (Salazar; Leihy, 2024). To address the impact of these costs on equity access to higher education, in 2016 the government introduced the so-called free policy or Gratuidad for lower-income students enrolled in accredited higher education institutions. Since 2018 Gratuidad has covered the tuition fees of students who belong to the lowest 60% of income groups (Chile, 2021). According to Espinoza et al. (2022), this freepolicy has contributed to equity of access. However, he pointed out that if admission only contemplates potential students’ academic records, which can be correlated with their socioeconomic level, this process will be less effective. Both Chile’s admission and tuition fee policies create a dual system with a group of universities for mass education and a small group of universities where the elite study (Villalobos; Quaresma; Franetovic, 2020; Quaresma; Villalobos, 2022).
Finally, an issue to take into account that might affect the expectations of completing university education among 15-year-olds is their chances of graduating from secondary school and higher education. As revealed by the secondary school completion rate indicator, the probability of graduation at this level is significantly higher in Chile than in Argentina. This probably explains why higher education enrolment among students corresponding to the lowest 30% of income is significantly higher in Chile than in Argentina. In addition, the chances of graduating from higher education are slightly higher in Chile than in Argentina (Table 1).
In sum, access to higher education in Argentina is concentrated in the open-access and tuition free public university and non-university sectors. In Chile, in contrast, access to the private sector predominates with elevated tuition fees and highly selective access procedures in an elite group of institutions. In terms of the chances of completing secondary and higher education, Chile is ahead of Argentina.
Method
Since there are no longitudinal surveys in Latin America, which follow the trajectory of the students from the secondary school level to their access and graduation from university, we use the microdata from the PISA Programme for the year 2022, which has not yet been used to analyse educational expectations in Argentina and Chile. This programme is carried out by the Organization for Economic Cooperation and Development (OECD), and its objective is to measure the competencies of 15-year-old students from different countries in order to evaluate how far they are prepared to tackle the challenges they will have to face as adults in society.
The PISA assessment not only focuses on student performance, but also collects data on the student’s family and institutional factors. It uses a two-stage sampling process. First, there is a random selection of schools in each country and then a second selection of students in each school. In addition to assessing literacy in certain subject areas, PISA 2022 collects contextual data based on three questionnaires: a student questionnaire, a parent questionnaire, and a school questionnaire. The first, administered to participating students, is a 30-minute questionnaire that covers student characteristics and family history. PISA 2022 incorporates information on educational expectations and students respond about the educational level they expect to complete. In turn, each student details the educational level achieved by his/her parents.
Methodological approach
In order to analyse the relationship between different factors, and the expectations of completing university education, we use a quantitative approach. We estimate a logistic regression model in which the dependent variable is a dichotomous variable that refers to the expectations of completing university studies. This model allows isolating the effects of each variable on the probability of having expectations; that means that the results show what happens when an explanatory variable varies ceteris paribus all the rest.
We estimate the following model:
Prob(Exp. of completing university)=F(Xb) (1)
Where:
The probability that student i has expectations of completing university is a dichotomous variable, which has a value equal to one if individual i declares that he/ she expects to complete university on finishing secondary school, and zero if the person declares that, he/she would continue studying in non-university higher education, working or not, only working or is undecided.
b is the vector of coefficients and X represents those observable explanatory variables corresponding to the characteristics of the student that may affect the probability of having university education expectations.
Variables
As we have mentioned previously, the dependent variable is a dichotomous variable, which refers to the expectations of completing university studies. The question of interest analysed is “Which of the following qualifications do you expect to complete”:
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Less than ISCED Level 2 (Lower secondary education)
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ISCED Level 2 (Lower secondary education)
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ISCED Level 3.3 (Upper secondary education with no direct access to higher education)
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ISCED Level 3.4 (Upper secondary education with direct access to higher education)
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ISCED Level 4 (Post-secondary non-higher education)
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ISCED Level 5 (Short-cycle higher education)
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ISCED Level 6 (Bachelor’s or equivalent)
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ISCED level 7 (Master’s or equivalent)
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ISCED Level 8 (Doctoral or equivalent)
The students that checked answers 7, 8 or 9 are considered as having university expectations.
Regarding the explanatory variables, those that influence educational expectations and which we analyse, are the following:
Gender: is a dichotomous variable, which has a value equal to one if the student is female and 0 otherwise.
Socioeconomic level of the student: we use the PISA index of economic, social and cultural status (ESCS) to build five quintiles. ESCS is a composite score that combines three components: parents’ highest level of education, parents’ highest occupational status and home possessions. The higher the value of ESCS, the higher the socio-economic status. ESCD increases with socio-economic status (SES). Then we follow Groisman’s (2016) classification and we refer to those who belong to the first quintile of per capita income as the lower SES; to those in the second, third and fourth quintile of per capita income as the medium SES; and to those who belong to the fifth quintile of per capita income as the high SES.
His/her academic performance: average of the plausible values of the score of Math, Language and Science of each student.
Primary repeater: Is a variable which has a value equal to one if the student repeated a grade during primary school and 0 otherwise.
Secondary repeater: Is a variable which has a value equal to one if the student repeated a grade during secondary school and 0 otherwise.
First generation student (FGS): Is a variable that shows whether the student’s parents are university graduates. It has a value equal to 1 if none of his parents has a university degree, and 0 otherwise.
Type of school attended: it has a value equal to 1 if the school attended is public and 0 if it is private
Cluster robust standard errors were estimated in order to control for the existence of potential violations of the standard assumptions, particularly heteroscedasticity (non-constant variance of errors), and clustered data -among schools e.g.
Test for the equality of estimates across models
In order to compare the results obtained for Argentina and Chile, we used the Seemingly Unrelated Estimation Test (SUEST) as outlined by Mize, Doan and Long (2019) which permits a statistically valid comparison of marginal effects across models fitted separately. The analysis was performed in Stata 17 using the mecompare package developed by Mize, Doan and Long (2019). All marginal effects are computed using only the sample specific observations.
Sample
The sample used in this analysis consists of 15-year-old students that attend school and have completed the individual survey in Argentina and Chile. Table 2 compares the main characteristics of the students in each country. In both cases, women represent nearly half of the sample. Argentina has more first generation students than Chile. On one hand, there are more repeaters in primary school in Chile than in Argentina, but on the other hand, there are more repeaters in secondary school in Argentina than in Chile. Additionally, Chile has a better academic performance in either Language or Math. Finally, Argentina has more 15-year-old students in the public sector (68%) than Chile (37%). The latter is in line with the increased privatization of education in Chile.
Data analysis
Table 3 shows the proportion of students that answered they had expectations of completing university studies in Argentina and Chile, and the simple correlation with the factors that may have some influence. Firstly, note that 72% in Argentina and 85% in Chile of secondary school students have expectations of completing higher education. This result is consistent with the greater chances that secondary school students in Chile have of completing higher education.
In accordance with the gap in favour of women in higher education enrolment rates in both countries, almost 76% of women in Argentina and 88% in Chile think that they are going to finish university studies, while this percentage decreases to 66% in the case of men in Argentina and 81% in Chile.
As was mentioned previously, students’ educational expectations appear to be related to the characteristics of the households. As the socioeconomic level of the students’ homes increases, the expectations of completing a university degree grows. In the case of students from low SES, 58% declare that they have these expectations in Argentina and 77% in Chile. In the case of students from homes with a medium SES, the expectations increase to 70% and 85% while for those students of the highest SES, the percentage grows to 83% and 93% for Argentina and Chile, respectively. These results are also consistent with the net higher education enrolment rate among low-income sectors in Chile compared to Argentina. At the same time, note that 68% of first-generation students in Argentina and 83% in Chile, have expectations of completing university studies, while that percentage increases to 78% and 89% for those who have at least one parent with a university degree. In the case of students who have repeated primary or secondary school, 51%
and 55%, respectively, think that they are going to complete university studies in Argentina; while 73% and 72% respectively expect to complete them in Chile. The score obtained by the student in the test appears to be related to his/her expectations. Both in Argentina and Chile, the average test score for those without expectations (395 and 400 respectively) is significantly lower than the one for those who have expectations (429 and 453 respectively). Regarding the type of school management, we observe that both in Argentina and Chile students that attend public schools have lower expectations than those who attend privately managed establishments, though the gap is bigger for Argentina (66% - 79% vs. 81% - 87%).
Results and discussion
Though the relationships between the variables seem quite strong, we would like to isolate the effects of the different factors in each country, in order to analyse separately each effect. In Table 4 we present the marginal effect of each variable after running a logistic regression, which shows the relationship between the variable and the likelihood of having expectations of completing university for Argentina and Chile. We present the marginal effect instead of the coefficients, since in the case of logistic regressions, the coefficients lack a direct interpretation. In the case analysed, we see, for example, the degree of association between gender and the probability of having expectations of completing university. Thus, we can observe that the gender gap is bigger in Argentina than in Chile. Hence, these results for Argentina and Chile are in line with the literature on the topic that has noted gender differences in educational expectations (Hillman, 2018). In this regard, after controlling for social origins and academic results, we obtain the same findings as Elias Andreu and Daza Pérez (2017, 2019) and Ali et al. (2022).
Isolating the effects of the different observable explanatory variables, we find that in Argentina, a greater difference is observed between the expectations of middle SES and High SES students compared to those from lower SES than in Chile. This finding suggests that those in the Argentine middle and upper classes, who are the most likely to graduate from secondary school in Argentina, are also the ones who have higher expectations of continuing higher education, and take advantage of the open access and tuition- free public higher education, rather than the students from the lower class. As we have noted, the proportion of secondary and higher education graduates is higher in Chile than in Argentina. OECD (2017) also notes the same results across all countries and economies and argues that the lack of role models and financial resources hinders the aspirations of disadvantaged students and may reduce the effort they invest in school.
Likewise, and as was anticipated, students with a higher academic performance are more likely to have expectations of completing university. This effect was also found by OECD (2017) for Argentina and other countries. In turn, repeaters are less inclined to have expectations than non-repeaters. This phenomenon is observed in both Argentina and Chile, although it is statistically significant only in the case of primary repeaters in Argentina. This result is in line with OECD (2017), which shows that this happens in the majority of countries. The relationship between secondary repeaters and educational expectations is not statistically significant for any of the countries analysed.
Regarding the type of management of the school that the student attends, we observe that both in Argentina and Chile, the fact that he/she attends a publicly managed school reduces the probability of having expectations of finishing university, though only in Argentina it is statistically significant. This is consistent with Elias Andreu and Daza Pérez’s (2017) findings for Spain, Jacobs and Wilder’s (2010) findings for the United States of America, and Chesters’ (2015) findings for Australia.
Concerning the statistical significance of the differences in the estimates between both countries, we can say with a 99% level of confidence that there are significant differences between the marginal effects related to gender and high SES of the student observed for Argentina and Chile. In both cases, the marginal effects are larger for Argentina, indicating a greater difference between women and men, as well as between high- and low-SES students. We also observed significant differences in the marginal effects of medium SES, primary repeater, and public school, in this case, with 90% confidence.
Conclusions
Our study, based on the PISA 2022 test, analysed the relationship between different characteristics of the students, their households, and their schools with their expectations of pursuing a university degree in Argentina and Chile.
Despite the higher academic and financial barriers to university entrance, Chilean secondary school students have higher expectations for completing university studies than their Argentine counterparts. It is likely that this result responds to Chile’s secondary and higher education graduation rate and the combination of a group of less selective university institutions and free university education for lower-income sectors under the Gratuidad policy. Nonetheless, in both Argentina and Chile, the student’s gender, socioeconomic level, grade repetition, and academic performance all influence the expectations of secondary school students. In Argentina, parents’ education and the type of school attended (public or private) also influence the expectations. In the comparison between Argentina and Chile, a greater difference is observed between the expectations of middle- and high-class students in Argentina compared to those from the lower class, than in Chile. These results are significant for the design of public policies that seek to improve the transition between secondary school and higher education. The international literature analysed showed that to further develop educational expectations through information about the supply of higher education institutions and programmes, as well as vocational guidance to secondary school students, it is vital to both optimize access for the most socioeconomically and socio-culturally disadvantaged sectors and increase their chances of graduation. According to research results from Ecuador (Castro et al., 2021), students’ limited and unequal access to information, as well as biased access, are among the factors that, along with socioeconomic factors and family context, contribute to the educational gap in accessing higher education. This conclusion is based on the asymmetry or lack of information among both students and parents, which causes some to overestimate the costs and underestimate the returns of education. Moreover, as was highlighted in the OECD report (2021), providing information to secondary school students about the careers associated with different degrees boosts their chances of finding jobs in the labour market. In particular, the study seeks to identify indicators that allow for anticipating better outcomes in the labour market. Among these indicators, linked to the decision to pursue higher education, it highlights the alignment of studies with career aspirations, like professional ones, and those that lead to tertiary-level studies. Then, in order to enhance the university expectations of the most disadvantaged secondary school students - economically and academically - it is just as important to help strengthen their academic performance, as it is to reinforce their ambitions and potential, that is, to create role models that their environment may lack.
Finally, it should be noted that using the PISA data source has both limitations and advantages for future research. Regarding the limitations, unlike a longitudinal survey, in which dimensions of analysis can be incorporated to better clarify the study of the process of constructing expectations for university studies, in the PISA test, we are constrained to use the variables for which information is collected. For example, longitudinal studies have shown an association between the expected rates of return on investment in higher education and the expectations of secondary school students to attend university (Gantier; Novella; Repetto, 2023; Menon et al., 2016).
As an advantage, the use of the PISA test allows us to continue advancing with our research, incorporating other Latin American countries into the analysis and comparing them with what happens in other more industrialized countries. This comparison will enable us to formulate better policies for vocational guidance and the provision of information on the options available to secondary school students, including institutions and programmes.
Data availability
The entire dataset supporting the results of this study is available in Repositorio Institucional Conicet Digital and can be accessed at https://datosdeinvestigacion.conicet.gov.ar/handle/11336/256624
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Editor:
PhD Fernando L. Cássio
