教育研究中的因果推断:对观察性横断面研究的因果关系进行分析
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https://doi.org/10.30827/relieve.v29i2.26843关键词:
技能, 教师培养, 学生, 学习计划摘要
事后回溯研究中的因果关系假设是社会科学研究方法领域普遍公认的问题。为了了解这一局限性,最近几年开始广泛地使用因果推断技术。这项技术是指通过一系列已建立的统计学过程从非实验研究中提取因果结论的技术。虽然该技术在社会科学和健康科学领域有着广泛的认知度和使用度,但在教育领域它还处在边缘位置。因此,该研究导入可用的主要因果推断技术,帮助教育研究者分析观察性面板数据。研究首先详述了倾向性得分匹配、工具变量、断点回归设计的主要特点和潜力,然后分别展示了这些技术在2018年国际学生评估项目(PISA2018)测试数据上的应用示例。在所有的建议模型中,数学能力都作为因变量出现。考虑到每项技术的特殊性,三种模型使用不同的自变量:在倾向性得分匹配模型中的幼儿教育出勤率;在工具变量模型中的学生学业期待以及断点回归设计中学校所在的城区规模。在考虑到教学研究需求和常规方法论应用过程的基础上,该研究还对一系列技术的潜力进行了讨论。
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