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Tytuł pozycji:

Population density in rural areas as a driver of the human capital development

Tytuł:
Population density in rural areas as a driver of the human capital development
Autorzy:
Polcyn, Jan
Czyżewski, Bazyli
Współwytwórcy:
Stanislaw Staszic University of Applied Sciences in Pila
Poznań University of Economics and Business
Data publikacji:
2017
Wydawca:
Aleksandras Stulginskis University
Słowa kluczowe:
educational effectiveness
ANOVA
human capital
rural areas
educational diversification
Język:
angielski
ISBN, ISSN:
9786094491283
18223230
23450916
Prawa:
http://creativecommons.org/licenses/by-nc-nd/3.0/pl/
Linki:
https://depot.ceon.pl/handle/123456789/14423  Link otwiera się w nowym oknie
Dostawca treści:
Repozytorium Centrum Otwartej Nauki
Książka
  Przejdź do źródła  Link otwiera się w nowym oknie
Rural areas are typically characterised by uneven access to education and the resulting varying levels of pupils’ educational attainment. The inefficiency of the education system may lead to a decreased level of human capital development in the society. It is therefore vital to identify the factors responsible for the inefficiency of the education system and take steps to mitigate their negative impact. The aim of the present study is to determine the relationship between the population density in rural areas, the pupils’ average level of examination performance and the educational value added. The analyses were based on the exam results achieved by lower secondary school-leavers in 1,372 rural communes between 2012 and 2014. The original intention was to include all rural communesin the analysis. However, due to the incompleteness of the data concerning some of the communes, they were eventually excluded from the study. The final sample for analysis consisted of about 58% of all rural communes in Poland. The communes were divided into classes, based on the criterion of population density. The objects under study were arranged in an ascending order according to the value of the population density variable, and then divided into four classes (class A contained 25% of communes with the highest population density). The classes thus defined were used as a qualitative predictor in the subsequently performed ANOVA test. As a next step, contrasts were determined by applying a simple contrast to the analysed classes of communes. The analyses revealed that the highest examination results were achieved in the communes with the highest population density, while the lowest examination results were found in the communes with the lowest population density. This dependence may be indicative of educational negligence at lower levels of education, in this particular case - at the stage of primary school. The results of the analyses point to the need for expanding the network of nursery schools. To address the above problem, financial support should be provided from the state budget to social initiatives aimed at increasing the access to nursery schools, e.g. by creating an appropriate system of subsidies for nursery schools run by both local governments and private entities.

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