Unlike the traditional statistical approaches, which imply the existence of a latent common causes that lead to the emergence and covariance of indicators, network modeling suggests that latent traits emerge due to interactions between indicators. Clearly, such kind of handling of the Program for International Student Assessment (PISA) results and other development indicators better reflect the mutual interactions of the indicators. By this aim, the network pattern of development indicators was revealed and graphically represented, most and least important indicators were detected. In addition, the indicators that have closer association with the PISA results were also detected. United Nations Development Program (UNDP) data were used for the analyzes. The 2015 year of data for sixty-six countries were used and consists of thirteen development indicators. The data were analyzed in R statistical program using “qgraph” package. The results showed that the PISA results are not at the central position compared to other development indicators while it was closely associated with gender inequality, secondary school completion rate and unequal life expectations. Those results were discussed based on the existing literature and some recommendations were given to policymakers and for future research.
Primary Language | English |
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Journal Section | Articles |
Authors | |
Publication Date | December 3, 2021 |
Published in Issue | Year 2021 |
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IJCER (International Journal of Contemporary Educational Research) ISSN: 2148-3868