Thinking spatially: reasons behind success in high school transition exam scores

Date

2023-7-10

Author

Şatana, Sibel

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

458
views

312
downloads

Cite This

The present study centres on the examination of the influence of socio-economic factors on scores of large scale national transition exam to high school institutions within all districts throughout Türkiye during the period spanning from 2015 to 2019 for examining spatial variations in this context. The exam scores were utilised as a proxy measure for the human capital of a given district. The present research argues that there exist spatial variations in the educational outcomes of districts, and a comprehensive understanding of the underlying reasons can be achieved through the integration of both quantitative and qualitative research methods in a sequential manner. Various non-spatial and spatial statistical techniques were employed to bolster arguments, including descriptive statistics, global and local spatial autocorrelation, Ordinary Least Square Regression (OLS), and Geographically-weighted Regression (GWR) in quantitative phase. The standard residual values from the OLS and GWR analyses and spatial autocorrelation statistics were evaluated together and it was decided to focus on the three identified districts to gain a comprehensive understanding of the reasons behind their success regarding exam scores. These districts were Piraziz in the province of Giresun, Dalaman in the province of Muğla, and Kayapınar in the province of Diyarbakır. The second phase of the study involved qualitative research in three districts, which was carried out by conducting in-depth interviews with educational stakeholders in each district. The interview forms were devised to comprehend the process by examining both internal and external factors. The classification of Internal Factors was comprised of four primary categories, namely social capital and local culture, collaboration, cooperation among institutions and location-specific employment opportunities. The assessment of external factors was conducted through the categorization of two primary themes: diaspora and the pulling effect, encompassing migration and gentrification. The findings of the comprehensive analyses are anticipated to provide a substantial contribution to the existing body of literature, offering guidance to education stakeholders and policy makers alike.

Subject Keywords

Human capital, Exam scores, Spatial autocorrelation, Spatial variation, Geographically weighted regression

URI

https://hdl.handle.net/11511/104734

Collections

Graduate School of Natural and Applied Sciences, Thesis