This study presents an educational performance assessment of Brazilian state-level units using the technique for order preference by similarity to the ideal solution (TOPSIS). Although this technique is a well-established multi-criteria decision making (MCDM) model that can be applied across diverse areas, it has yet to be applied to an analysis of primary and secondary education. We assess how state-level units in Brazil perform in terms of primary and secondary educational inputs and outputs during the period from 2013 to 2017. We handle epistemic uncertainty with regard to weight definition using maximal information entropy. Additionally, a Tobit regression approach on performance scores is developed. Results show that region of the country plays an important role in determining educational performance. Moreover, results indicate that gross domestic product (GDP) is positively related to education scores while infant mortality is negatively associated with educational performance.

中文翻译：

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巴西的州级教育绩效：采用治理视角的 MCDM 方法

本研究使用与理想解决方案相似的顺序偏好技术 (TOPSIS) 对巴西州级单位进行教育绩效评估。尽管这项技术是一种成熟的多标准决策 (MCDM) 模型，可以应用于不同的领域，但它尚未应用于小学和中学教育的分析。我们评估了 2013 年至 2017 年期间巴西州级单位在小学和中学教育投入和产出方面的表现。我们使用最大信息熵处理关于权重定义的认知不确定性。此外，还开发了一种关于性能分数的 Tobit 回归方法。结果表明，该国的地区在决定教育绩效方面起着重要作用。而且，