Factors Associated with Expectations of Studying a University Degree in Argentina

In their final years of high school, teenagers decide on their future education and career path. This is a crucial time when decisions are made that will affect the course of their lives, and it is possible to observe the extent to which socioeconomic and educational characteristics in the home and previous school performance influence their choices.

The information available to make this decision also affects the chances of accessing quality higher education, which provides tools for upward social mobility and improved quality of life for young people who are most economically and socially vulnerable (OECD, 2018).

The expectations formed at the high school level regarding the continuation of studies will also influence the future social and academic integration of new students into the institution and degree program they have chosen. Some studies have shown that expectations of academic and intellectual development had a direct and positive influence on students' commitment to the institution and their intentions to complete their degree (Cabrera and La Nasa, 2000; Cole, 2017).

In particular, research conducted in Canada found that having aspirations to continue higher education during high school was as important as the cognitive training acquired at this level for subsequent academic performance in higher education (Christofides et al., 2015). Having high educational expectations reduces the risk of early school dropout (Ou and Reynolds, 2008) and increases both academic performance (Choi, 2018; Hao and Bonstead-Burns, 1998) and the likelihood of completing university studies (Andrew and Flashman, 2017). In order to design public and institutional policies that promote equal opportunities in access to higher education, it is important to pay attention to the development of educational and career aspirations among high school students. In this regard, Choi (2018) points out that changes in expectations have a significant impact on educational and career trajectories, which is why knowledge of the factors associated with expectations is also useful for the design of educational policies.

In the context of Latin America, this issue takes on particular relevance. The massification of higher education in the region is driven especially by high school graduates who live in economically and culturally disadvantaged households (Avitabile, 2017).

The objective of this study was to analyze the factors that influence expectations regarding continuing university studies. To this end, the national assessment tool “Aprender” developed by the Ministry of Education of Argentina and applied in a census-like manner in 2019 to students in their final year of high school was used as a data source. It should be noted that this is a topic that has not yet been explored in Argentina.

1.1 Factors explaining the construction of educational expectations

In order to identify the factors that may influence students' expectations regarding higher education, we analyzed sociological approaches that allowed us to investigate the answer to the question that guided this study.

According to Bourdieu (1989), agents and groups of agents are defined by their relative positions in the social fabric according to the volume and structure of different types of capital: economic, cultural, and social. To explain the decisions made by high school students and their families, there is particular interest in cultural capital in its embodied state, known as habitus. Bourdieu (2007) points out that habitus is the framework of perception and evaluation, in terms of cognitive and evaluative structures, that people acquire in their socialization process based on their position in the social world. Habitus is an internal structure undergoing constant restructuring. Therefore, there is room for the agent to make decisions, conditioned by class habitus, which guides those decisions. This would explain different school investment strategies according to class habitus. The dominant classes, which hold greater economic, cultural, and social capital, tend to develop strategies of heavy investment in education because they seek to reproduce their class status. Families with greater cultural and social capital have more information about academic fields and the reputation of different educational institutions, enabling them to implement successful school investment strategies. On the contrary, students from the most disadvantaged classes are channeled into disciplinary fields and institutions with less social prestige (Bonnewitz, 2003).

Boudon (1983) also pointed out that the social class of students influences the decision-making process regarding the choice of career and institution in which to study, but his explanation points more to the rationality of the agents within this social framework than to the power of social reproduction exercised by the action of the school and the social environment. Boudon begins by noting that educational inequality exists to the extent that a student's social background influences their academic performance.

The opportunity gap, which occurs especially in the early years of education within the family, is related to the unequal distribution of economic, cultural, and social resources in households according to social class. Boudon (1983) referred to this effect on social inequality in education as the “primary effect,” but he also pointed out that the social background of students subsequently affects the decision-making process regarding the paths to follow in high school and their future in higher education. This occurs even when students achieve the same level of academic performance. Students with high academic performance but belonging to the most disadvantaged social classes choose educational options that are less academically demanding and preferably vocational or technical in nature. On the contrary, students belonging to higher socioeconomic and cultural classes, with equal or even lower academic performance, reveal high academic and professional ambition. They therefore choose to study university degrees that enjoy greater social prestige. According to Boudon, this advantage in educational achievement that upper-class youth can attain is due to the socialization process in an environment with abundant economic and cultural resources. Boudon called this educational inequality, which results from the decision-making process that varies according to social class among students with equal academic performance, a “secondary effect.”

The explanation for why this side effect occurs was provided by Breen and Goldthorpe's (1997) rational expectations model. According to the authors, young people, together with their families, calculate the benefits, costs, and risks when evaluating investment in higher education, with the central goal of avoiding downward social mobility. In this case, young people from lower socioeconomic backgrounds choose to study at higher education institutions and programs that do not involve high costs in economic and academic terms, given that their objective is to maintain the social position achieved by their family and obtain economic returns equivalent to those of this family group. In the cost-benefit analysis, these students and their families weigh the time they must devote to studying instead of working, and the economic and employment risks of not completing their university studies. In contrast, the middle and upper classes have higher aspirations, seeking to obtain a university degree and favoring the most prestigious careers, emulating the academic achievements of their families and peer groups. To maintain or improve their class position, they must invest in university education and in those institutions and careers with high-value credentials in the labor market.

Taking the same approach, Barone et al. (2018) criticize one of the assumptions of rational actor theory (perfect information for agents) and incorporate into the model developed by Breen and Goldthorpe (1997) the existence of misperceptions among students and their families due to a lack of information when deciding where and what to study. Thus, they point out that there are two information barriers in the decision-making process regarding which type of institution and degree program to select. The first barrier is educational: lower socioeconomic sectors opt for more vocational or technical degree programs because they believe that academic degree programs are more demanding in terms of difficulty and time commitment to study. The second barrier is employment-related: these more socially and economically disadvantaged sectors believe that if they do not complete their university studies (which are generally longer), they will not be able to find work.

Using data from a survey conducted in Italy among middle school students, Barone et al. (2018) analyzed these misperceptions. Based on the information provided by the survey, they selected students with good academic performance whose parents had not attained a higher education degree and who did not indicate that they would choose the academic track in upper secondary school, which is an option in Italian secondary education. The researchers then randomly selected a group who were told that a team of education experts wanted to inform them that, based on their children's school results, they had the academic skills necessary to successfully choose the academic pathway. They were also told that if they chose the academic pathway, their children would improve their chances of obtaining a university degree. In addition, they were informed that the academic option was as good as the other vocational options in terms of job market prospects, in case students did not wish to pursue university studies after finishing high school. A control group that did not receive this information was also selected. After a year, interviews were conducted with students in the treatment group and those in the control group to find out what their final decision was regarding the path they had chosen. As a result of the experiment, parents who received better information about the real risks of choosing the academic path that leads to university, versus the vocational option, increased their choice of the academic path.

In the approaches examined, the main variable explaining students' expectations and choices is social class. Another highly relevant variable is parental education, which has a strong influence on the choice of high school. This choice can be decisive in determining subsequent success in continuing university studies versus vocational or technical studies, and even in the career path chosen (Chesters, 2015). This occurs due to the presence of horizontal stratification in higher education, since institutions and careers are ranked on a scale of prestige, reputation, quality, and, in some cases, cost of tuition (Triventi et al., 2020). This horizontal ranking of institutions and degree programs in terms of prestige, quality, and access, in socioeconomic terms, affects the status of higher education as a public good (Maldonado-Maldonado and González, 2018). In this regard, a study conducted in Spain shows that between 2003 and 2018, vertical inequality—that is, the gap according to socioeconomic strata—in the aspirations of high school students to continue their studies at the university level decreased. However, the horizontal spread increased. More and more young people from lower-income families with low levels of education aspired to pursue vocational studies (Valdés, 2021). Regarding this finding, a survey conducted in eight countries by the OECD (2018) in Finland, Belgium, France, Israel, the Netherlands, Norway, Sweden, and the United States showed that students with mothers and fathers with lower levels of education were overrepresented in vocational programs.

There are also gender inequalities in expectations regarding higher education. Elías and Daza (2019) indicate that, in recent decades, women's access to higher education has increased. In the case of men, their grades, educational success, and expectations are higher, even among students with similar social backgrounds and academic results. In addition, Merino and Martínez (2012) show that women are more likely to choose university education and men are more likely to choose vocational training.

Another dimension analyzed is whether the high school is public or private. A study conducted in Barcelona reveals that this dimension was significant in explaining students' choice of what type of studies to pursue. The advantage of attending a private school, as opposed to a public school, is assumed to be related to the social composition of the student body and the likely effect of peers on the construction of expectations (Elias and Daza, 2017).

Based on this background, a wealth of literature has emerged analyzing the factors associated with educational expectations. In Spain, Choi (2018) studied these factors using logistic models. He found a high correlation between expectations and academic performance, socioeconomic and educational status of households, and peer expectations. Based on the results obtained, the author recommends improving policies to positively influence educational expectations, such as targeted measures to combat socioeconomic inequalities, coupled with reducing socioeconomic segregation and incorporating school counselors.

The source of information used in this study is the database of Argentina's national “Aprender” (2019) assesment (Ministry of Education and Culture, 2019). The program collects data on student educational performance from standardized tests, as well as providing complementary information on family and school characteristics that allows for the contextualization of student results.

The analysis focused on the census-style questionnaire administered in 2019 to students in their final year of high school. In September of that year, the knowledge acquired in the areas of language, arts and mathematics was assessed for 5th/6th-year secondary school students. The sample used in this analysis consisted of 282,532 students in their final year who completed 50% or more of an assessment and the individual questions used in this analysis.

The question of interest analyzed was: “What are you going to do when you finish high school?”, which allowed for six possible answers: (i) continue studying in tertiary education, (ii) continue studying at university, (iii) work and continue studying in tertiary education, (iv) work and continue studying in university education, (v) work, and (vi) I don't know yet.

Upon completing secondary education in Argentina, graduates, regardless of their field of study and whether they attended a general or technical school, have formal access to undergraduate or degree programs offered by higher education institutions. In this case, they can choose to study one of the degree programs offered at the 67 state universities and university institutes or at the 64 private universities and university institutes. They can also decide to study at one of the 2,270 non-university higher or tertiary institutes, which offer teacher training and short technical degree programs (Ministry of Education and Culture, 2019, 2021). Studying in any field in the public sector is free, while in the private sector there are fees. With the exception of some courses offered in public and private institutions, admission mechanisms are not selective, as students do not have to take entrance exams if there are places available for a particular course (Fernández et al., 2018).

2.1 Analysis Methodology

A logistic regression model of the probability of university expectations was used to study the relevance of each factor associated with the probability of having expectations of continuing university education. To this end, the parameters of the following model were estimated:

prob (university expectation_i ) = F ( X_i β) (1)

Where the probability that student i would expect to continue studying in higher education is a dichotomous variable, which has a value of one if student i states that upon completing secondary education they will continue studying in higher education or working and studying in higher education, and zero if the student states that they will continue studying in higher education, only working, or is undecided. β is the coefficient vector and X represents those observable explanatory variables corresponding to the characteristics of the student that affect the probability of having expectations of continuing to study in higher education. These are:

• Woman: has a value of 1 if the student self-identifies as a woman and 0 if they self-identify as a man.
• Low socioeconomic status1 (SES): has a value of 1 if the student belongs to a household with low socioeconomic status and 0 otherwise.
• Medium SES: has a value of 1 if the student belongs to a household with a medium socioeconomic status and 0 otherwise.
• High SES: has a value of 1 if the student belongs to a household with a high socioeconomic status and 0 otherwise.
• First generation: this variable has a value of 1 if neither parent has a university education and 0 if either parent has reached this level.
• Language score: score obtained in the 2019 Aprender test in the area of Language.
• Mathematics score: score obtained on the 2019 Aprender test in the area of mathematics.
• Repeater: this is a dichotomous variable that has a value of 1 if the student declares that they have repeated the same grade twice or more in primary or secondary school.
• Public school: has a value of 1 if the educational institution attended by the student is public and 0 if it is private.

Based on the relevant variables reported in the international literature and discussed in the previous section (García de Fanelly and Adrogué, 2015), in addition to the information provided by Aprender, the following variables were included in the model: gender, grade repetition, household socioeconomic status, parents' education, academic performance, and type of school.

Using the Stata 15 statistical package, the multinomial logistic model was estimated using microdata from the Aprender database (Aprender, 2019), which is a census of students in their final year of high school. In this model, the independent variable is not dichotomous (university expectations yes or no), but can take on four different values (Paz and Cid, 2012): continuing university studies, working or not working; continuing tertiary studies, working or not working; working only; and still undecided. This model allows us to capture the relationship between different factors and young people's non-academic expectations. Upon completing high school, the last level of compulsory education, young people can choose between different alternatives. Although most of them have academic expectations or expect to go to university, there is a range of non-academic options from which young people can choose. This model allows us to analyze the relationship between student characteristics, gender, socioeconomic and cultural background, academic performance in high school, and the type of school where students in their final year of high school study, with the expectations they have after completing this level.

The data referring to descriptive statistics, extracted from the Aprender census (2019), are presented below. Table 1 shows that 67% of high school students planned to continue their studies in university education, while 17% planned to continue in tertiary education. This high level of aspiration to continue higher education in Argentina could be related to non-selective access and free undergraduate and graduate studies in the state sector. On the other hand, only 5% chose to work exclusively, 12% of students were undecided, and 38% planned to study higher education and work at the same time. The latter figure corresponded to the national average of university students in public universities who were working: 39% in 2019 (Ministry of Education and Culture, 2019).

In turn, it was observed that 71% of women considered continuing their studies at university, while in the case of men, this percentage decreased to 61%. In the case of repeat students, who represented one in five, half (50%) chose to continue studying at university and a quarter (24%) in tertiary education. In the case of non-repeaters, at least 7 out of 10 chose to pursue university studies, and only 1.5 out of 10 opted for tertiary studies. These results show how the choice of post-secondary studies is conditioned by gender and the academic trajectory of the student body.

The socioeconomic and cultural level of the student's household influenced the decision-making process in academic choice. Table 2 shows that as the socioeconomic level of households rises, as well as the cultural capital of students' families, interest in pursuing a university degree increases. Conversely, expectations of pursuing a tertiary education decline as students' socioeconomic status increases. Only 7% of students from high socioeconomic status households expressed expectations of continuing their studies in tertiary education, while that percentage rises to 17% and 28% for students from middle and low socioeconomic status households, respectively. It is also interesting to note that 60% of first-generation students, defined as those with parents who have no college education, expected to continue their studies at the university level. That percentage rose to 82% for those with a parent who has a college education. It was also observed that a higher proportion of students in private schools had anticipated continuing their studies in higher education compared to students in public schools. The latter showed greater interest in continuing their studies in tertiary programs managed by private schools.

Academic performance also appeared to be related to expectations of university or tertiary education, as shown in figures 1 and 2. Of the students with advanced results in language, 84% expected to pursue a university degree, and among those with advanced results in mathematics, 90% expected to pursue a university degree.

In summary, descriptive statistics showed results consistent with those reported in the literature reviewed. In particular, expectations regarding pursuing university studies varied according to gender, household socioeconomic status, parents' educational level, previous academic trajectory, type of school, and academic performance on language and mathematics tests.

3.1 Results of applying logistic regression models

Table 3 describes the results of the logistic regression models used to determine the incidence of factors on the probability of having expectations of continuing to study in higher education.

In the case of logistic regressions, the coefficients lack a direct interpretation. Therefore, we chose to present the odds ratio, which is defined as the measure of association between a condition, in this case the expectation of continuing to study at university, occurring in one population group compared to the possibility of it occurring in another. In the case analyzed, for example, the degree of association between a person's gender and the likelihood of having expectations of continuing on to university was identified. Thus, it was observed that women were more likely than men to have expectations of continuing their studies at the university level. For every 171 women who planned to pursue university studies, 100 men considered this option possible.

For its part, household socioeconomic status showed that the higher the level, the greater the probability of having expectations of moving on to university education. Individuals belonging to the middle socioeconomic level were 1.84 times more likely to have expectations of continuing their studies at university than those in the low level. It should be noted that this level is omitted, and all statistics for the other levels refer to the difference with respect to this level. Thus, subjects with a high socioeconomic status were 2.8 times more likely (than those with a low status) to have expectations of continuing their studies in higher education.

Likewise, it was identified that families' cultural capital (Bourdieu, 1989) and parents' academic preparation (Barone et al. 2018; Boudon, 1983) have an impact on educational expectations. Students whose parents had completed university studies had higher expectations for higher education than those whose parents had not reached this level of education. The results also confirmed that students' educational expectations are conditioned by their position in the social structure. These findings are consistent with the conclusions of previous studies that the higher the socioeconomic and educational level of parents, the higher their educational expectations (Elias and Daza, 2019). Consequently, the coefficients referring to the socioeconomic status and education of parents captured what Boudon (1983) called the “secondary effect.” Thus, regardless of the student's academic performance, it was noted that students living in households with higher socioeconomic status and whose parents have a high level of education have more opportunities to continue their university studies than those belonging to more disadvantaged social groups.

In turn, students with higher academic performance in both language and mathematics were more likely to have expectations of continuing their studies at university, which Boudon (1983) referred to as the “primary effect.” Likewise, as expected, repeat students were less likely (compared to non-repeat students) to have expectations of continuing their studies at university. With regard to the type of school the student attends, as Elias and Daza (2017) pointed out, attending a public school reduced the likelihood of having expectations of continuing university education.

In addition, the probability of young people choosing to pursue tertiary education rather than university education, deciding to work only, or even not having decided yet, was analyzed. A multinomial logistic model was used, omitting the category: pursuing university education. The coefficients compare the relationship between a given characteristic—such as being female or having a high SES—and the probability of pursuing tertiary education versus university education, or working instead of pursuing university education, or not having decided yet.

The results of the multinomial logistic model confirm that, in Argentina, students' educational expectations are conditioned by their position in the social structure. The higher the socioeconomic level, the lower the probability of pursuing tertiary education rather than university education, or of working exclusively or not having decided. Elias and Daza (2019) point out that there are clear differences in academic expectations based on social origin. According to Becker and Hecken (2009), children of middle-class parents tend to choose academic paths, while those of working-class parents lean toward vocational training.

As can be seen in Table 4, women were less likely to expect to pursue tertiary education, work only, or be undecided. In other words, they are more likely to choose university studies. This result is consistent with what Merino and Martínez (2012) have already mentioned about women's greater propensity to choose academic paths.

Students who repeated a year were more likely to pursue tertiary education, work full-time, or be undecided about their future plans. It can also be observed that the higher the performance in language and mathematics, the greater the likelihood that the young person plans to continue studying at university.

Table 4 shows significant differences in students' expectations related to the type of school they attend. This finding for Argentina corresponds to that found by Elías and Daza (2017) in Barcelona. The researchers found that institutional dynamics play a relevant role in educational transitions, and that these are significantly different for students in public schools compared to those attending private-subsidized schools, due both to the social composition of the student body in each school and to institutional dynamics related to assessment or guidance processes.

In this study, we analyzed the different factors that influence students' expectations in terms of their academic aspirations upon completing high school in Argentina. In particular, we studied the relationship between students' expectations of continuing their university studies and certain personal characteristics, such as gender and academic performance, their home environment, such as the socioeconomic and cultural level of their parents, and their school, as well as the type of school, public or private. The topic studied is relevant given that, as international literature shows, the expectations formed at the secondary level regarding the continuation of studies affect the future social and academic integration of new students into university and the chosen career.

Based on logistic regression models, we have found that educational expectations in Argentina are conditioned, on the one hand, by the socioeconomic status of the student's household. The higher the socioeconomic status, the less likely the student is to choose to pursue tertiary education rather than university education, or to work exclusively, or to be unsure of what to do after finishing secondary school. On the other hand, we identified that university expectations are higher for women, for those who have not repeated any year of schooling, for those who attend private schools, for those with parents with higher educational levels, and for those with better academic performance.

These results highlight the importance of incorporating measures in high school that contribute to improving the information available to students, so that their decisions about continuing their studies are not conditioned by the socioeconomic and cultural characteristics of their homes, gender, previous educational background, or academic performance. In this way, it would be possible to help narrow the social inequality gap in young people's educational choices for the future.

Likewise, given the influence of household socioeconomic status on students' educational expectations, the availability of scholarships for access to higher education can help reduce the likelihood of early dropout (Adrogué and García de Fanelly, 2018). Although the amounts of these scholarships do not usually cover the opportunity cost of studying without working, they can prevent students from vulnerable sectors from combining their studies with long working hours, which affects their probability of remaining in higher education.

One limitation of this study is that Argentina does not have longitudinal surveys, such as those used in some of the international studies discussed herein. These surveys make it possible to analyze the extent to which the expectations of students in their final year of high school have materialized in terms of effective access to higher education. According to Choi (2018), having longitudinal data facilitates a deeper understanding of the relationship between household socioeconomic status and academic performance and educational expectations, as well as the dynamic process of expectations throughout the final years of high school and the first years of postsecondary education. These longitudinal surveys could also incorporate a dimension not available in the database used in this study: career choice. As noted in the international literature, career choice is also influenced by the socioeconomic and cultural level of the household and has important consequences for students' academic and professional future, and in general for their mobility within the social structure. In contexts with high percentages of the population in situations of social and economic vulnerability, as is the case in Latin American countries, enriching the information available so that young people can make an appropriate career choice is central to increasing opportunities for improving the quality of life of the most socially disadvantaged youth.

Translation: Leslie Ann Serrano

Authorship contribution

Cecilia Adrogué: conception and design (33%), data analysis (50%).

Ana García de Fanelli: conception and design (33%).

Eugenia Orlicki: conception and design (33%), methodology and data analysis (50%).

Conflict of interest statement

The authors have no conflicts of interest to declare.

Source of funding

The research has not received any funding.

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