Predicting resident satisfaction with public schools in small town Iowa

Predicting resident satisfaction with public schools in small town Iowa
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预测爱荷华州小镇居民对公立学校的满意度

DOI:
10.1002/sta4.517
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发表时间:
2023
期刊:
影响因子:
1.7
通讯作者:
Zarecor, Kimberly
Zarecor, Kimberly
中科院分区:
数学4区
文献类型:
--
作者:
Batista, Ricardo;Zhu, Zhengyuan;Peters, David;Zarecor, Kimberly

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估计居民对公共教育的满意度在公共行政中有很大的用处,特别是在不断缩小的小社区的决策者中。但这种估计通常是通过调查获得的,调查成本很高,而且由于答复率低,在高空间分辨率下往往不可靠。我们的研究发现,小社区居民对公立学校的满意度可以在社区层面使用公共数据进行合理估计。几个模型充分概括了看不见的数据,这些模型通常包括以下协变量:国家学生评估分数,学校重组,净开放招生,以及相对于邻近地区的教育成果的成本。因此,我们的研究结果相当于一个具有成本效益的调查替代测量满意度与公立学校在小爱荷华州社区。
Estimates of resident satisfaction with public education have great utility in public administration, especially among decision makers in shrinking small communities. But such estimates are typically obtained via surveys, which are costly and often unreliable at high spatial resolutions given low response rates. Our study found that satisfaction with public schools among residents of small communities can be reasonably estimated at the community level using public data. Several models generalized adequately to unseen data—these models typically included the following covariates: state student assessment scores, school reorganizations, net open enrollment, and the cost of educational outcomes relative to neighboring districts. Our findings thus amount to a cost‐effective survey alternative for gauging satisfaction with public schools in small Iowa communities.
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