The performance of education systems in the light of Europe 2020 strategy

Stumbrienė, Dovilė; Camanho, Ana S.; Jakaitienė, Audronė

doi:10.1007/s10479-019-03329-5

Cited by 26 publications

(20 citation statements)

References 47 publications

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“…The literature reports numerous methodologies for creating composite indicators (CI) to measure effectiveness, although they can also be used for other purposes such as providing a big picture of multidimensional processes, which can be used to guide public policies, for instance (Saltelli, 2007). CI add different subindicators into a single summary measure that gives an idea of the status of a system (Stumbriene et al, 2019). The Joint Research Centre-European Commission (2008) handbook covers most of the methods for constructing CI; some of the most noteworthy are the AHP (analytic hierarchy process) (Milutinović et al, 2014), the PCA (principal component analysis) method (Gómez-Limón and Riesgo, 2009), gray relation analysis (Lee and Lin, 2011), the Delphi method (Galo et al, 2014) and BoD (benefit of the doubt) (Melyn and Moesen, 1991;Cherchye et al, 2007b).…”

Section: The Proposed Methodology: Measuring Education Effectivenessmentioning

confidence: 99%

Evaluation and determinants of preschool effectiveness in Chile

Giménez

Thieme

Prior

et al. 2022

Socio-Economic Planning Sciences

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Early intervention in quality education is a way to equalize opportunities, a premise assumed by several countries that has increased interest in preschool education, which is now a relevant area of public policy. However, the performance of preschool education centers has received relatively scarce research attention. Consistent with the above, there are no studies quantifying the level of effectiveness with which these centers operate. This study examines the problem and aims to evaluate the performance of preschool education centers that serve children from lower socioeconomic families in Chile. For this, a centralized DEA Assurance Region model is proposed, which, in addition to avoiding the main criticisms received by the traditional Benefit of Doubt models, shows important differences in the results of efficacy and weights of the composite indicators. In addition, a second stage analysis is carried out using decision trees to identify variables that determine the composition of homogeneous preschool groups according to their effectiveness. The target population evaluated is kindergartens serving families with low socioeconomic status in urban and rural areas in Chile, and results reveal the importance of three structural factors: family income, kindergarten size, and location.

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Section: The Proposed Methodology: Measuring Education Effectivenessmentioning

confidence: 99%

Evaluation and determinants of preschool effectiveness in Chile

Giménez

Thieme

Prior

et al. 2022

Socio-Economic Planning Sciences

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“…Thus, the four-clusters solution confirms the stability of clusters of the strongest and weakest countries. 3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,21,22,24,25,26,27,28 Ireland 7 0.4729 1,2, 3,4,5,6,7,8,9,10,11,12,14,15,16,17,18,19,20,21,22,24,25,26,27,28 Bulgaria 2 0.4448 1,2, 3,4,5,…”

Section: Countries Clustering Solutionmentioning

confidence: 99%

“…There have been a number of publications on Europe 2020 strategy in the last few years. In many publications, the authors suggest comparable composite indicators to assess the performance of the Member States with respect to implementation of the goals described by the Europe 2020 strategy-see, for example, [2][3][4][5][6][7][8][9][10][11].…”

Section: Introductionmentioning

confidence: 99%

“…Some articles do not cover the trends in progress of all headline indicators, but only certain optional indicators have been selected. The authors were interested in these areas of Europe 2020 strategy development: the performance of education systems [3,12], poverty and social exclusion [16], research and development management [14], unemployment [17], resource efficiency [8], issues of the labor market, income disparities and poverty [18], and greenhouse gas emissions [13].…”

Section: Introductionmentioning

confidence: 99%

“…Research methods most often used in articles are as follows: statistical methods [2,9,14,15,17,19,20], multiple-criteria decision making [4,8,10,11], the DEA (data envelopment analysis) method [3,18], and fuzzy goal programming [7].…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the Europe 2020 Strategy Implementation Using Interval Entropy and Cluster Analysis for Interrelation between Two Groups of Headline Indicators

Kosareva

Krylovas

2021

Entropy

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The research analyzes the progress of Member States in the implementation of Europe 2020 strategy targets and goals in 2016–2018. Multiple criteria decision-making approaches applied for this task. The set of headline indicators was divided into two logically explained groups. Interval entropy is proposed as an effective tool to make prioritization of headline indicators in separate groups. The sensitivity of the interval entropy is its advantage over classical entropy. Indicator weights were calculated by applying the WEBIRA (weight-balancing indicator ranks accordance) method. The WEBIRA method allows the best harmonization of ranking results according to different criteria groups—this is its advantage over other multiple-criteria methods. Final assessing and ranking of the 28 European Union countries (EU-28) was implemented through the -cut approach. A -means clustering procedure was applied to the EU-28 countries by summarizing the ranking results in 2016–2018. Investigation revealed the countries–leaders and countries–outsiders of the Europe 2020 strategy implementation process. It turned out that Sweden, Finland, Denmark, and Austria during the three-year period were the countries that exhibited the greatest progress according to two headline indicator groups’ interrelation. Cluster analysis results are mainly consistent with the EU-28 countries’ categorizations set by other authors.

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