Does taking additional Maths classes in high school affect academic outcomes?

被引:1
作者
Priulla, Andrea [1 ]
Vittorietti, Martina [1 ]
Attanasio, Massimo [1 ]
机构
[1] Univ Palermo, Palermo, Italy
关键词
Educational data; Multi-level propensity score; Caliper matching; Multi-state Markov model; PROPENSITY SCORE; SOCIAL INEQUALITIES; HIGHER-EDUCATION; UNIVERSITY; STRATIFICATION; EXPANSION; CHOICE;
D O I
10.1016/j.seps.2023.101674
中图分类号
F [经济];
学科分类号
02 ;
摘要
Several studies in the mathematical education literature show the effect of students' high school skills in maths on their success at higher levels of education and work. In particular, the importance of maths course taking in US high schools is highlighted to be important for college enrollment and completion. The choice of taking additional maths courses or, as in Italy, of choosing a high-school curriculum with more maths, is not random: it depends on several substantial factors such as gender and socio-economic status. This selection bias implies that the differences in the academic outcomes might be traceable not only to mathematics ability and knowledge. In this paper, the aim is to estimate the treatment effect of attending a relatively new high school curriculum in Italy with more maths, with respect to the traditional track of the scientific "liceo", on two academic outcomes: university enrollment and first-year university performance. After having reduced the selection bias using a caliper multi-level propensity score matching procedure, a multi-state Markov model is used to study the treatment effect on the joint educational outcomes.
引用
收藏
页数:9
相关论文
共 42 条
[1]  
Agasist T., 2012, Res Appl Econ, V4, P33, DOI [DOI 10.5296/RAE.V4I2.1316, 10.5296/rae.v4i2.1316]
[2]  
Agresti Alan., 2013, CATEGORICAL DATA ANA, V3rd
[3]   Propensity score matching with clustered data. An application to the estimation of the impact of caesarean section on the Apgar score [J].
Arpino, Bruno ;
Cannas, Massimo .
STATISTICS IN MEDICINE, 2016, 35 (12) :2074-2091
[4]   The specification of the propensity score in multilevel observational studies [J].
Arpino, Bruno ;
Mealli, Fabrizia .
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2011, 55 (04) :1770-1780
[5]  
Attanasio M, 2021, RAPPORTO POPOLAZIONE
[6]   An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies [J].
Austin, Peter C. .
MULTIVARIATE BEHAVIORAL RESEARCH, 2011, 46 (03) :399-424
[7]   Optimal caliper widths for propensity-score matching when estimating differences in means and differences in proportions in observational studies [J].
Austin, Peter C. .
PHARMACEUTICAL STATISTICS, 2011, 10 (02) :150-161
[8]  
Ballarino G, 2021, SOCIOLOGIA ISTRUZION
[9]   Social stratification, secondary school tracking and university enrolment in Italy [J].
Ballarino, Gabriele ;
Panichella, Nazareno .
CONTEMPORARY SOCIAL SCIENCE, 2016, 11 (2-3) :169-182
[10]   School expansion and uneven modernization. Comparing educational inequality in Northern and Southern Italy [J].
Ballarino, Gabriele ;
Panichella, Nazareno ;
Triventi, Moris .
RESEARCH IN SOCIAL STRATIFICATION AND MOBILITY, 2014, 36 :69-86