Corona Gaps: Vulnerable students’ mathematics competencies before and after the pandemic and practices of resilience-supporting teachers

在德国的学校系统中，社会在数学成绩上的差距比经合组织的平均水平要大。许多专家假设，在大流行期间部分学校关闭期间，这些差距进一步扩大，但到目前为止，经验支持有限。此外，人们对那些表现出韧性的弱势学生以及在大流行期间支持这种韧性的教学做法知之甚少。在日冕缺口项目中，将通过比较大流行前后背景因素对数学成绩的影响(RQ1)，确定背景因素以及家庭教育条件是增加还是减少与大流行有关的脆弱性(RQ2)，确定有许多有韧性的学生的最佳实践班级(RQ3)，以及确定教师在这些最佳实践班级中使用的支持复原力的实践(RQ4)，来检验和证实社会差距扩大的假设。该项目重新分析了在大流行前后已经或将从两个五年级学生样本(n=2×500)和两个七年级学生样本(n=2×1 200)中收集的测试数据，其中许多是城市地区学校的弱势学生。对于RQ1和RQ2，两个双样本在协调多水平回归模型中比较了社会经济地位、移民身份、性别、语言水平和家庭教育条件等背景因素对数学成绩的预测能力。对于RQ3，一个样本的纵向设计将揭示大流行期间学习的得失以及促进或阻碍它们的学习机会的更多洞察。在95名教师中，采用重复测量的协方差分析来确定最佳实践班，以便在RQ4中，最佳实践教师可以在问卷和访谈中被问及他们支持复原力的教学实践。由于主要的数据收集是在或将在其他项目中进行的，所以这个补充项目只需要额外的关于学生家庭教育条件和教师自我报告做法的问卷项目，随后将进行密集的中学比较分析。补充项目预期的结果是对社会差距扩大假说的经验性见解，提供了一个独特的证据，不仅包括关于学生在不同数学能力和潜在脆弱性因素中与流行病相关的脆弱性的细粒度特定主题知识，而且还包括对韧性的高度相关方面的见解：有助于韧性的背景因素和家庭教育条件将与支持学生韧性的教学实践一起被确定。这种对恢复力的关注不仅可以描述与大流行相关的挑战，还可以为未来克服挑战的指导方法提供信息。

In the German school system, social gaps in mathematics achievement are larger than the OECD average. Many experts have hypothesized that these gaps have further increased during the partial school closures during the pandemic, but so far there has been limited empirical backing. Furthermore, little is known about those vulnerable students who have shown resilience and the teaching practices that support that resilience during the pandemic. In the Corona Gaps project, the hypothesis of increased social gaps will be tested and substantiated by comparing the impact of background factors on mathematics achievement before and after the pandemic (RQ1), identifying background factors and whether home-schooling conditions increase or reduce pandemic-related vulnerability (RQ2), identifying best-practice classes with many resilient students (RQ3), and determining resilience-supporting practices used by teachers in these best-practice classes (RQ4). The project re-analyzes test data that have been or will be gathered from two samples of fifth graders (n = 2 x 500) and two samples of seventh graders (n = 2 x 1 200) before and after the pandemic, many of them vulnerable students in schools in urban areas. For RQ1 and RQ2, the two double samples are compared in coordinated multilevel regression models, with respect to the predictive power of the background factors of socioeconomic status, immigrant status, gender, language proficiency, and the home-schooling conditions for the mathematics achievement. For RQ3, a longitudinal design in one sample will reveal additional insights into the learning gains or losses during the pandemic and the learning opportunities that fostered or hindered them. Covariance analysis with repeated measures will be used to identify the best-practice classes among 95 teachers, so that for RQ4, best-practice teachers can be asked for their resilience-supporting teaching practices in questionnaires and interviews. As the main data gathering was or will be administered within other projects, only additional questionnaire items on students’ home-schooling conditions and teachers’ self-reported practices will be necessary for this supplemental project, which will be followed by an intensive secondary comparative analysis.Expected outcomes of the supplemental project are empirical insights into the increased social gaps hypothesis, providing a unique substantiation that comprises not only fine-grained topic-specific knowledge about students’ pandemic-related vulnerability in different mathematical competencies and potential vulnerability factors, but also insights into highly relevant aspects of resilience: Background factors and home-schooling conditions contributing to resilience will be identified along with teaching practices that can support students’ resilience. Rather than only describing pandemic-related challenges, this focus on resilience can also inform instructional approaches for overcoming challenges in the future.