The effect of districts’ social development on student performance

Giménez, Gregorio; Martín-Oro, Ángel; Sanaú, Jaime

doi:10.1016/j.stueduc.2018.05.009

Cited by 21 publications

(25 citation statements)

References 40 publications

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“…More thorough explanation of the features is presented in the paper of F. Unal 7 . Influence of social features on students' performance is also discussed in [3][4][5].…”

Section: Resultsmentioning

confidence: 99%

The impact of e-learning and social parameters on students’ academic performance

Petrusevich¹

2020

Science for Education Today

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Introduction. The article examines the problem of assessing students' academic performance in the current situation. The purpose of the paper is to evaluate the influence of e-learning and some social and behavioral parameters on students’ academic performance. Materials and Methods. The author employed the machine learning procedures in order to identify and assess the current problems of the educational system, students’ behavior, and universities’ policy. Methods of mathematical analysis and statistics as well as ensemble methods (gradient boosting and the random forest algorithms) were used in order to achieve high accuracy of the research. Results. The author conducted the analysis of the following datasets devoted to academic performance at higher and secondary educational institutions in a number of countries: Students’ Performance in Portugal, E-learning Student Reactions and Students’ Academic Performance. The purposes of the current study were to identify statistical correlations between social parameters of students and the level of their academic performance and to understand how academic performance is determined by the implementation of online learning and blended learning. The research findings suggest that mathematical statistics and data analysis methods allow to identify correlations between students’ performance data and reveal hidden relationships which can be important for university staff. Conclusions. In conclusion, the author summarizes the results of evaluating the impact of the introduction of e-learning elements and some social parameters on students’ academic performance. Keywords Clustering students; Blended learning; Academic performance evaluation; Digitalization of education; Digital technologies in education; Correlation of features; performance improvement.

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“…More thorough explanation of the features is presented in the paper of F. Unal 7 . Influence of social features on students' performance is also discussed in [3][4][5].…”

Section: Resultsmentioning

confidence: 99%

The impact of e-learning and social parameters on students’ academic performance

Petrusevich¹

2020

Science for Education Today

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“…In a first step, we carried out a nonparametric Shapley-Owen-Shorrocks decomposition to compute the relative importance of happiness, comparing it with other traditional factors, to explain the variance in SLE. This technique has been used mostly in economics to understand the causes of inequality and poverty [40,41] and, recently, it has been used in other fields, such as economics of education or economic growth [42][43][44][45]. Nevertheless, to the best of our knowledge, it has not been applied, until now, in health economics, in spite of its methodological advantages.…”

Section: Methodsmentioning

confidence: 99%

Is Happiness Linked to Subjective Life Expectancy? A Study of Chilean Senior Citizens

2021

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The main goal of this research is to determine the link between happiness and individual subjective life expectancy (SLE) among Chilean senior citizens. We use data from the 2015 edition of the Chilean Social Protection Survey. Our sample consists of 1298 seniors: 700 aged 65–74, 421 aged 75–84, and 177 aged 85 and older. We provide a novel methodological approach that allows us to measure the relative contribution of happiness to SLE, by combining the Shapley–Owen–Shorrocks decomposition with contrasts of marginal linear predictions of the equality of the means by groups. Results reveal that happiness is the most important determinant of seniors’ SLE, and the effect is stronger the older the people are. Addressing varying levels of happiness is important because both happiness and unhappiness have a significant impact. In an ageing population, social agents should consider that these variables (happiness and SLE) are related to engagement in healthy lifestyles. If prevention programs integrated this interaction, welfare systems could save scarce resources. Therefore, governments should foster happiness to support active ageing.

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“…Although these decomposition techniques have been used in different fields in economy, they have hardly been applied to the empirical study of economic growth, in spite of their advantages. These techniques have been used, for example, to understand the causes of inequality and poverty [14,15] and differences in wages [16,17] and in educational achievement [18][19][20][21][22][23]. Firstly, they make possible the quantification of the relative contribution of explanatory variables and, therefore, the identification of which factors have contributed the most to economic growth.…”

Section: Introductionmentioning

confidence: 99%

The Use of Decomposition Methods to Understand the Economic Growth Gap between Latin America and East Asia

2021

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Understanding how growth factors contribute to explaining the large differences in growth rates across countries remains an important research agenda. The common approach to exploring this issue is based on the use of multiple linear regression analyses. This work contributes to growth literature by applying a new perspective based on the use of variance decomposition procedures: Shapley–Owen–Shorrocks and Oaxaca–Blinder. These methodologies have four main advantages with respect to traditional methodologies: they make possible the quantification of the relative contribution of each factor to economic growth, they allow us to estimate the efficiency in the use of the endowments of each factor, they can be used with any functional form and they can be used with estimation methods that are robust regarding endogeneity issues. We illustrate these advantages by analyzing the causes of the economic growth gap between Latin America and East Asia over the period 1980–2014. We find that the economic growth divergence between the two regions can be primarily explained by the differences in institutions and physical capital. In addition, the results indicate that the higher East Asian performance is not only due to its higher levels of endowments in these factors, but also to the higher efficiency in its use. We connect our results with the 2030 Agenda for Sustainable Development.

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The effect of districts’ social development on student performance

Cited by 21 publications

References 40 publications

The impact of e-learning and social parameters on students’ academic performance

The impact of e-learning and social parameters on students’ academic performance

Is Happiness Linked to Subjective Life Expectancy? A Study of Chilean Senior Citizens

The Use of Decomposition Methods to Understand the Economic Growth Gap between Latin America and East Asia

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