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Spatial variations of school-level determinants of reading achievement in Italy
Visualization in Engineering Pub Date : 2021-06-09 , DOI: 10.1186/s40536-021-00105-5
Chiara Sacco , Patrizia Falzetti

The study of the territorial difference in educational achievement is a widely debated topic, in particular in Italy for the presence of the well-known strong regional disparities. National and international large scale assessments confirmed that the main characteristic of the Italian school system is the geographical cleavage between North and South. Policymakers have pressing needs to find solutions to reduce geographical disparities. In this study, we investigate the spatial disparities of academic achievement from a new perspective, assuming that the relationship between academic achievement and predictors varies across Italy. Our aim is to examine the extent of the spatial disparities in the relationship between academic achievement and some school-level factors related to inequalities in educational outcomes, moving beyond the regional administrative confines, in order to identify new spatial patterns. We exploited the reading standardized tests administered by INVALSI in 2018–2019 focusing on the 8th-grade students. Crucial to our contribution is the use of the geographically weighted regression and the k-mean clustering, which allows studying the spatial variability of the impact of the school-level factors on academic achievement and to gather schools in new spatial clusters. The findings of this paper demonstrate the necessity to design a more specific education policy and support the identification of the main critical factors for different geographical areas.

中文翻译:

意大利学校水平决定因素的空间变化

对教育成就的地域差异的研究是一个广泛争论的话题,尤其是在意大利,因为存在众所周知的强烈区域差异。国内和国际的大规模评估证实,意大利学校体系的主要特征是南北之间的地理鸿沟。政策制定者迫切需要找到减少地域差异的解决方案。在这项研究中,我们假设学业成就与预测因素之间的关系在意大利各不相同,从一个新的角度调查学业成就的空间差异。我们的目的是检查学业成绩与一些与教育成果不平等相关的学校层面因素之间关系的空间差异程度,超越区域行政范围,以识别新的空间模式。我们利用了 INVALSI 在 2018-2019 年针对 8 年级学生实施的阅读标准化测试。对我们的贡献至关重要的是使用地理加权回归和 k 均值聚类,它允许研究学校层面因素对学业成绩影响的空间变异性,并将学校聚集在新的空间集群中。本文的研究结果表明有必要设计更具体的教育政策并支持确定不同地理区域的主要关键因素。对我们的贡献至关重要的是使用地理加权回归和 k 均值聚类,它允许研究学校层面因素对学业成绩影响的空间变异性,并将学校聚集在新的空间集群中。本文的研究结果表明有必要设计更具体的教育政策并支持确定不同地理区域的主要关键因素。对我们的贡献至关重要的是使用地理加权回归和 k 均值聚类,它允许研究学校层面因素对学业成绩影响的空间变异性,并将学校聚集在新的空间集群中。本文的研究结果表明有必要设计更具体的教育政策并支持确定不同地理区域的主要关键因素。
更新日期:2021-06-09
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