Session Information
Paper Session
Contribution
Higher education has become central for the economic and social development of countries. As the systems expanded, an increasingly heterogeneous student body entered higher education and challenges related to quality and equity emerged (Unesco, 2021). Equity implies that social class, ethnicity, geographical location or other characteristics should not determine students’ access and success. Yet, different socioeconomic backgrounds tend to be reproduced in differentiated academic achievements, with the less privileged students having poorer grades or dropping out more frequently (Tavares et al, 2022). The difference in achievement and academic success between lower SES students and higher SES students has been widely addressed in the literature (Li & Carroll, 2019; Kahu & Nelson, 2018). These differences may be linked with the different mechanisms through which students acquire and use social capital and support (Mishra, 2020). As higher education is not an isolated experience, but rather entails persistent support and encouragement from family, peers, community, neighbourhood, and faculty), it is important to understand the extent to which some contextual factors might influence academic achievement.
Several studies have sought to understand the relationship between academic achievement and these contextual factors. An important contextual factor influencing the learning process and academic achievement is the pedagogical interaction between students. The impact of these interactions is known in the literature as ‘contagion’, ‘neighbourhood effects’ or ‘peer group effects’ (Ding & Lehrer 2007). It generally means that students’ academic achievement may be influenced by the characteristics and behaviours of their peers. Peer effects – the term used in this study – can therefore be defined as the impact of the study group on the learning environment and on the individual academic performance (Illanes, 2014; Guadalupe & Gonzalez-Gordon, 2022). The effects of peers seem larger for minority and disadvantaged students, with scarce access to resources or opportunities to develop the study habits needed to succeed. Peer group abilities have considerable positive effects on students’ academic performance as they tend to have higher academic achievement if the quality of their peer group is higher (Ding and Lehrer, 2006; Zimmerman 2003; Vandenberghe, 2002; Sacerdote, 2001). Many other studies have found that top ability peers had a positive influence on others’ outcomes (Griffith & Rask 2014; Sacerdote 2001; Carrell et al., 2009). The interaction between peers supports and motivates students to achieve a higher cognitive level and to find a personal meaning for learning (Dempsey, Halton, & Murphy, 2001).
This paper will focus on Brazilian higher education, a country where inequalities are still huge in various sectors of society. Despite affirmative actions and positive discrimination policies (Bertolin and McCowan, 2022), higher education remains a stratified system (elitist courses and courses which mostly attract disadvantaged students). Inequalities also persist in academic progression, retention and attainment. Focusing on the attainment of disadvantaged undergraduate students, this paper aims to examine whether these students might benefit from interaction with peers of high socioeconomic and cultural capital (Griffith & Rask 2014). For that purpose, the study compares the academic achievement of disadvantaged students in cohorts with different degrees of socioeconomic diversity: homogeneous cohorts of low SES students, in which peers are mainly from the same low socioeconomic and cultural background; heterogeneous cohorts, in which peers are both from high and low socioeconomic backgrounds; and homogeneous cohorts of high SES students, in which peers are mainly from a high socioeconomic and cultural background. The hypothesis to be tested in this study is that the academic achievement of underprivileged students who complete their studies tends to be better in cohorts in which the number of students with high sociocultural capital is higher.
Method
Every year, students completing undergraduate programmes in specific disciplinary areas take a nationwide test called ENADE (the National Test of Student Performance). It is a mandatory graduation requirement for all summoned students each year. However, the exam evaluates the higher education system and does not influence students’ final grade. It evaluates students’ performance and also gathers data on their socioeconomic background. This study uses the ENADE database which contains microdata on the students’ performance and on the social, economic and cultural conditions of each participant. Participation can reach nearly 500,000 students each year. Data from a complete 3-year cycle of ENADE assessment are employed (2014, 2015 and 2016), the last cycle for which data are available on individual students. It covers more than 1 million students from courses of different disciplines and the dataset is a representative sample of the total of 8.6 million students enrolled in Brazilian higher education (the 4th largest in the world). To verify the influence of social capital and peer group effect on the academic achievement of disadvantaged students, descriptive statistics and general linear models (ANOVA) are used, with exam performance as the dependent variable. Social capital and the type of cohort in which the student is enrolled (low SES cohorts, heterogeneous cohorts, and high SES cohorts) are the independent variables. First, a SES score was calculated for each student based on family income, mothers’ educational level and type of secondary school (public or private), ranging from 0 (lowest) to 45 (highest). Then the students were divided into four groups according to the SES score quartiles, in which Q1 students were those with the lowest SES. In order to classify cohorts into the three categories above, the entropy (degree of heterogeneity of the cohorts) was calculated, as proposed by Shannon (1948). Cohorts with high entropy were classified as heterogeneous and cohorts with low entropy were classified as low SES homogeneous or high SES homogeneous, according to the level of concentration of students from different SES backgrounds. Only face-to-face cohorts with 10 or more students were considered. Variables related to the school effect were used for control purposes and to avoid bias in the results. Analysis of Variance (ANOVA) was performed to compare the results of low SES students (quartile Q1) in the ENADE General Education and Specific Component tests in the three types of cohorts (low SES homogeneous, heterogeneous and high SES homogeneous).
Expected Outcomes
The first results confirm the hypothesis advanced in this study. When considering the General Education component, which is common to all disciplinary areas in the same year, the comparison of the performance of Q1 students in the different cohorts revealed that they perform best when they are in cohorts classified as high SES homogeneous. In fact, performance is higher for Q1 students in heterogeneous cohorts compared to Q1 students in low SES homogeneous ones and is also higher for Q1 students in high SES homogeneous cohorts compared to Q1 students in heterogeneous cohorts. Considering the Specific Component of the exam, which differs by disciplinary area, similar results were found. When controlling for disciplinary area, Q1 students enrolled in high SES homogenous cohorts continue to perform better that their counterparts enrolled in low SES homogeneous and heterogeneous cohorts. These preliminary results show that disadvantaged students seem to perform better in cohorts which are predominantly made up of students coming from privileged backgrounds, benefiting from the interaction with peers of high socioeconomic and cultural capital. Further detailed analyses by disciplinary area will be performed.
References
Bertolin, J., & McCowan, T. (2022). The Persistence of Inequity in Brazilian Higher Education: Background Data and Student Performance. In Tavares, O. Sá, C. Sin, C. Amaral, A., (Eds.) Equity Policies in Global Higher Education (pp. 71-88). Palgrave Macmillan, Cham. Carrell, S. E., Fullerton, R. L., & West, J. E. (2009). Does your cohort matter? Measuring peer effects in college achievement. Journal of Labor Economics, 27(3), 439-464. Dempsey, M., Halton, C., & Murphy, M. (2001). Reflective learning in social work education: Scaffolding the process. Social work education, 20(6), 631-641. Ding, W., & Lehrer, S. F. (2007). Do peers affect student achievement in China's secondary schools?. The Review of Economics and Statistics, 89(2), 300-312. Griffith, A. L., & Rask, K. N. (2014). Peer effects in higher education: A look at heterogeneous impacts. Economics of Education Review, 39, 65-77. Guadalupe, M., & Gonzalez-Gordon, I. (2022). Bias From Enrollment: Peer Effects on the Academic Performance of University Students in PUCE Ecuador. Journal of Hispanic Higher Education, 15381927221085679. Illanes, G. (2014). Peer effects: What do we really know? Centro de Estudios Públicos. https:// www.cepchile.cl/cep/site/artic/20160304/asocfile/20160304100733/pder377_GIllanes.pdf Kahu, E. R. & Nelson, K. (2018). Student engagement in the educational interface: understanding the mechanisms of student success. Higher Education Research & Development, 37(1), 58-7. Li, I. W & Carroll, D. R. (2019). Factors influencing dropout and academic performance: an Australian higher education equity perspective. Journal of Higher Education Policy and Management, (), 1–17. Mishra, S. (2020). Social networks, social capital, social support and academic success in higher education: A systematic review with a special focus on underrepresented’ students. Educational Research Review, 29, 100307. Sacerdote, B. (2001). Peer effects with random assignment: Results for Dartmouth roommates. The Quarterly journal of economics, 116(2), 681-704. Shannon, Claude E. (1948). A mathematical theory of communication, Bell System Technical Journal. 27(3): 379–423. doi:10.1002/j.1538-7305.1948.tb01338.x http://cm.bell-labs.com/cm/ms/what/shannonday/shannon1948.pdf Tavares, O., Sá, C., Sin, C., & Amaral, A. (2022). Equity Policies in Global Higher Education: Reducing Inequality and Increasing Participation and Attainment. Cham: Springer Nature. Unesco (2021). Thinking higher and beyond: Perspectives on the futures of higher education to 2050. Paris: UNESCO IESALC. Vandenberghe, V. (2002). Evaluating the magnitude and the stakes of peer effects analysing science and math achievement across OECD. Applied Economics, 34(10), 1283-1290. Zimmerman, D. J. (2003). Peer effects in academic outcomes: Evidence from a natural experiment. Review of Economics and statistics, 85(1), 9-23.
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