Educational Progress of Children at Risk of Low Academic Achievement: A Psychometrically Informed Investigation of Educational Outcomes and Resilience Factors with Longitudinal Data of the National Educational Panel Study

处于危险环境中的具有复原力的儿童在许多领域都有正常的发展结果，包括教育和认知发展；与此同时，那些缺乏适应力的人落后于同龄人。几项纵向研究在弹性框架下追踪了高危儿童的发展，但缺乏包括德国儿童在内的高质量研究。国家教育小组研究（NEPS）通过纵向数据和测试理论的方法进步，为弹性和教育成果的研究提供了一些独特的特点。NEPS包括德国几个高危群体和非高危儿童的大规模纵向数据。该数据允许识别和比较当前研究特别感兴趣的三个风险群体：低社会经济地位（SES）家庭，有移民背景的儿童和有特殊教育需求（SEN）的学习者。此外，NEPS的大型数据集允许对分析测试项目的方法进行改进。由于高危人群的人口统计和其他差异，个别测试项目可能无法为高危儿童和非高危儿童提供相同的信息（即，它们缺乏测量不变性）。这将使准确比较高危儿童的教育和认知发展结果的问题进一步复杂化。为了解决这些问题，我们建议在NEPS数据集中确定三个高危群体，包括低社会经济地位、移民背景和SEN学习者，并通过数学、科学、拼写和元认知能力纵向分析他们的发展。我们将使用一种新的差异项目函数（DIF）分析来量化NEPS项目在风险儿童和非风险儿童中不不变的程度。最后，使用合理的值，我们将产生发展的定量纵向模型，如潜在增长、轮廓和变化模型，以确定预测风险学习者的弹性的因素。这项工作将为心理弹性研究和项目反应理论（IRT）方法论做出重大贡献，并为研究人员使用NEPS或类似大规模研究中的量表来比较风险儿童和非风险儿童提供实践指导。

Children in at-risk circumstances with resilience have normal developmental outcomes in many areas, including education and cognitive development; meanwhile, those who lack resilience lag behind their peers. Several longitudinal studies have tracked the development of at-risk children in the resilience framework, but high quality studies including German children are lacking. The National Education Panel Study (NEPS) offers some unique features for both the study of resilience and educational outcomes with longitudinal data and methodological advances in test theory. NEPS includes large-scale longitudinal data of several at-risk groups as well as not at-risk children in Germany. . This data allows for identification and comparison of three at-risk groups of particular interest to current research: low socioeconomic status (SES) families, children with migrant background, and learners with special educational needs (SEN). Additionally, the large dataset of NEPS allows for a refinement of methodology for analyzing test items. Because of demographic and other differences in at-risk populations, individual test items may not provide the same information for both at-risk and not at-risk children (i.e., they lack measurement invariance). This would further complicate the problem of accurate comparing educational and cognitive development outcomes for at-risk children. We propose to address these problems by identifying three at-risk groups including low SES, migrant background, and learners with SEN in the NEPS dataset and analyze their development longitudinally via competencies in math, science, and spelling as well as metacognition. We will use a novel differential item function (DIF) analysis to quantify the extent to which NEPS items are not invariant across both at-risk and not at-risk children. Finally, using plausible values we will produce quantitative longitudinal models of development, such as latent growth, profile, and change models for both groups to identify factors that predict resilience in at-risk learners. This work will contribute significantly to both resilience research and item response theory (IRT) methodology, as well as provide practical guidance to researchers using scales included in NEPS or similar large-scale studies for the comparison of at-risk children with those not at-risk.