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on Education |
| By: | Granja, Cintia Denise (UNU-MERIT, Maastricht University, and Institute of Geosciences, University of Campinas); Visentin, Fabiana (UNU-MERIT, Maastricht University) |
| Abstract: | In this study, we examine the impact of exchange programs’ timing on students’ academic performance, focusing on the moment in which students travel and the length of the period spent abroad. To provide causal evidence, we exploit unique data of more than 10,000 students from a well-known and internationalized Brazilian university from 2010 to 2020. By combining Propensity Score Matching with Difference in Differences techniques, we find that international mobility impacts groups of students differently. Students who travel closer to the end of their undergraduate courses benefit the most from the mobility experience (an increase of 0.06 points on final standardized grades), while negative effects (-0.05 points) are found for those who travel at the beginning of their university program. Our results also show that, while student mobility impacts positively and significantly students who participate in programs lasting from one semester to one year (0.08 points), negative effects are associated with shorter periods abroad (-0.1 points). |
| Keywords: | Tertiary education, international student mobility, academic performance, grades, student achievement, propensity score matching, difference in differences |
| JEL: | I23 I26 J24 O15 O34 |
| Date: | 2021–12–14 |
| URL: | http://d.repec.org/n?u=RePEc:unm:unumer:2021049&r= |
| By: | Contini, Dalit; Di Tommaso, Laura; Muratori, Maria Caterina; Piazzalunga,Daniela; Schiavon, Lucia (University of Turin) |
| Abstract: | Italy was the first Western country hit by Covid-19 in February 2020, responding with a tight lockdown and full school closure until the end of the school year. This paper estimates the effect of the pandemic and school closure on the math skills of primary school pupils in Italy. We compare the learning achievements of two cohorts of pupils, the pre-Covid and the Covid cohort. For both cohorts, we match scores on the national standardised assessment in grade 2 with scores on a standardised test delivered by the researchers at the end of grade 3. The pandemic had a large negative impact on the pupils’ performance in mathematics (-0.19 standard deviations). Among children of low-educated parents, the learning loss was larger for the best-performing ones (up to -0.51 s.d.) and for girls (-0.29 s.d.). |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:uto:dipeco:202117&r= |
| By: | Deborah A. Cobb-Clark (The University of Sydney, School of Economics); Tiffany Ho (ARC Centre of Excellence for Children and Families over the Life Course); Nicolás Salamanca (Melbourne Institute: Applied Economic & Social Research, the University of Melbourne) |
| Abstract: | We use quasi-experimental variation in the timing of national standardized test-score reports to estimate the causal impact of giving parents objective information about children’s academic achievement. Releasing test scores leads to more modest perceptions of academic achievement and reduced school satisfaction. The use of private tutoring is increased, while extracurricular activities are reduced. Examining the underlying mechanisms, we show that it is public-school parents and parents of children receiving unexpectedly “bad” test scores who alter their perceptions. Learning that a child scores above the national average raises perceived academic achievement and time devoted to education, while reducing leisure time. |
| Keywords: | Parental investments, test-score information, parental perceptions, overconfidence |
| JEL: | I21 J13 D10 D90 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:iae:iaewps:wp2021n17&r= |
| By: | Andrew E. Clark (PSE - Paris School of Economics - ENPC - École des Ponts ParisTech - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique - EHESS - École des hautes études en sciences sociales - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, PJSE - Paris Jourdan Sciences Economiques - UP1 - Université Paris 1 Panthéon-Sorbonne - ENS Paris - École normale supérieure - Paris - PSL - Université Paris sciences et lettres - EHESS - École des hautes études en sciences sociales - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement); Huifu Nong (Guangdong University of Finance & Economics); Hongjia Zhu (Jinan University [Guangzhou]); Rong Zhu (Flinders University [Adelaide, Australia]) |
| Abstract: | The COVID-19 pandemic has led to widespread school shutdowns, with many continuing distance education via online-learning platforms. We here estimate the causal effects of online education on student exam performance using administrative data from Chinese Middle Schools. Taking a difference-in-differences approach, we find that receiving online education during the COVID-19 lockdown improved student academic results by 0.22 of a standard deviation, relative to pupils without learning support from their school. Not all online education was equal: students who were given recorded online lessons from external higher-quality teachers had higher exam scores than those whose lessons were recorded by teachers from their own school. The educational benefits of distance learning were the same for rural and urban students, but the exam performance of students who used a computer for online education was better than those who used a smartphone. Last, while everyone except the very-best students performed better with online learning, it was low achievers who benefited from teacher quality. |
| Keywords: | COVID-19 pandemic,Online education,Student performance,Teacher quality |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:hal:pseptp:halshs-03467128&r= |
| By: | Aurélien Sallin; Simone Balestra |
| Abstract: | The majority of recent peer-effect studies in education have focused on the effect of one particular type of peers on classmates. This view fails to take into account the reality that peer effects are heterogeneous for students with different characteristics, and that there are at least as many peer effect functions as there are types of peers. In this paper, we develop a general empirical framework that accounts for systematic interactions between peer types and nonlinearities of peer effects. We use machine-learning methods to (i) understand which dimensions of peer characteristics are the most predictive of academic success, (ii) estimate high-dimensional peer effects functions, and (iii) investigate performance-improving classroom allocation through policy-relevant simulations. First, we find that students' own characteristics are the most predictive of academic success, and that the most predictive peer effects are generated by students with special needs, low-achieving students, and male students. Second, we show that peer effects traditionally reported by the literature likely miss important nonlinearities in the distribution of peer proportions. Third, we determine that classroom compositions that are the most balanced in students' characteristics are the best ways to reach maximal aggregated school performance. |
| Keywords: | peer effects, high dimensionality, machine learning, classroom composition |
| JEL: | C31 H75 I21 I28 |
| Date: | 2022–01 |
| URL: | http://d.repec.org/n?u=RePEc:iso:educat:0189&r= |
| By: | Marina Lagemann (Justus-Liebig-University Giessen); Peter Winker (Justus-Liebig-University Giessen) |
| Abstract: | An important role is ascribed to students’ social networks in explaining both social and ethnic differentials in educational achievement and attainment. For example, students’ social networks are assumed to influence their probability of success by providing educationally-relevant resources and by promoting effort and educational investments. The direction and strength of the network’s effect on students’ educational success is assumed to depend on the network’s precise characteristics, such as educational and migration background. As track selection by school performance (as is the case in Germany) goes hand in hand with a segregation of students by characteristics like social and migration background, it can be assumed that educational success itself has an influence on the social resources students have access to at later stages of their educational careers. Given the complexity of instruments commonly applied in self-administered questionnaires to assess students’ social resources, the quality of data on measures of network characteristics is likely to depend on the respondents’ abilities. As regards the estimation of the association between network characteristics and educational success, biased measurement of social network characteristics apparently constitutes a challenge as spurious correlation may be observed between measures of educational achievement and network characteristics if the bias systematically correlates with education. We report empirical findings on a complex instrument used in a self-administered questionnaire applied in the National Educational Panel Study (NEPS) to 9th-graders in the classroom, which was designed to measure the social resources young people have at their disposal at the point of transition from general into vocational education. The data allows identifying population subgroups who face particularly strong difficulties in completing the relevant set of questions in a consistent way. Specifically, this selection can be shown to be significantly correlated with different measures of educational achievement as well as with the respondents’ migration background. As the network characteristics we investigate, i.e., the network members’ educational and migration background, have been found to correlate with students’ educational success, ignoring this selection can be shown to heavily bias estimates of the association between educational achievement and social network characteristics. |
| Keywords: | Social networks; network characteristics; network composition; social resources; answering behavior; cognitive skills; measurement bias; migration background; educational success; educational attainment |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:mar:magkse:202202&r= |
| By: | Adel Daoud |
| Abstract: | Enabling children to acquire an education is one of the most effective means to reduce inequality, poverty, and ill-health globally. While in normal times a government controls its educational policies, during times of macroeconomic instability, that control may shift to supporting international organizations, such as the International Monetary Fund (IMF). While much research has focused on which sectors has been affected by IMF policies, scholars have devoted little attention to the policy content of IMF interventions affecting the education sector and childrens education outcomes: denoted IMF education policies. This article evaluates the extent which IMF education policies exist in all programs and how these policies and IMF programs affect childrens likelihood of completing schools. While IMF education policies have a small adverse effect yet statistically insignificant on childrens probability of completing school, these policies moderate effect heterogeneity for IMF programs. The effect of IMF programs (joint set of policies) adversely effect childrens chances of completing school by six percentage points. By analyzing how IMF-education policies but also how IMF programs affect the education sector in low and middle-income countries, scholars will gain a deeper understanding of how such policies will likely affect downstream outcomes. |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2201.00013&r= |