专家对教育系统特征的判断:一个新的数据集

Claudia Traini
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引用次数: 2

摘要

本文的中心目标是描述和发布从34个经合组织成员国(奥地利、比利时、保加利亚、克罗地亚、塞浦路斯、捷克共和国、丹麦、爱沙尼亚、芬兰、法国、德国、希腊、匈牙利、冰岛、爱尔兰、以色列、意大利、拉脱维亚、立陶宛、卢森堡、荷兰、挪威、波兰、葡萄牙、罗马尼亚、俄罗斯、斯洛伐克、斯洛文尼亚、西班牙、瑞典、瑞士、土耳其、乌克兰和英国)的教育系统专家调查中收集的数据。为了对教育系统进行分类,学者们确定了四个概念:分层、职业专一、标准化和集中化。虽然近年来提供了数值指标,但它们要么存在测量误差,要么存在理论概念与经验指标之间联系不紧密的问题。相比之下,这个新的数据集是基于对每个概念的最重要维度的识别,这些概念已经在许多国家进行了操作和一致的测量。这些指标是根据2016年对206名专家进行的调查收集的信息构建的。填写问卷的专家有来自不同学科的学者和研究人员,也有学校校长和教育部工作人员等从业人员。他们是通过学术网络、阅读学术出版物和互联网搜索来确定科学协会或研究中心的成员来选择的。除了总结回复率的一般统计数据并提供这个新数据集的详细描述外,本文还将每个指标与文献中最常用的指标进行了对比。一节还专门讨论了关于使用专家的假设和怀疑。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Expert Judgements on Education Systems’ Characteristics: A New Dataset
The central goal of this paper is to describe and release the data collected from an expert survey on education systems of 34 OECD member states (Austria, Belgium, Bulgaria, Croatia, Cyprus, Czech Republic, Denmark, Estonia, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Israel, Italy, Latvia, Lithuania, Luxembourg, the Netherlands, Norway, Poland, Portugal, Romania, Russia, Slovakia, Slovenia, Spain, Sweden, Switzerland, Turkey, Ukraine and the United Kingdom). To classify education systems, scholars have identified four concepts: stratification, vocational specificity, standardization and centralization. Although numerical indicators have been provided in the last years, they all suffer from either measurement error or weak connection between theoretical concept and empirical indicant(s). In contrast, this new dataset is based on the identification of the most important dimensions of each concept that have been operationalized and measured consistently for a large number of countries. The indicators have been constructed upon information gathered from a survey of 206 experts carried out in 2016. The experts who completed the questionnaire are academics and researchers from different disciplines but also practitioners such as school principals and staff of the ministry of education. They were selected through academic networks, a reading of scholarly publications and internet searches to identify members of scientific associations or research centres. In addition to summarizing general statistics on the response rate and providing a detailed description of this new dataset, in this paper each indicator is contrasted against the ones most often employed in the literature. A section is also dedicated to the discussion of the assumptions and doubts surrounding the use of expert.
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