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

处于风险环境中的儿童，具有复原力，在许多领域都有正常的发展成果，包括教育和认知发展;同时，那些缺乏复原力的儿童落后于同龄人。一些纵向研究跟踪了风险儿童在弹性框架中的发展，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）提供了一些独特的功能，无论是弹性和教育成果的研究与纵向数据和测试理论的方法进步。 NEPS包括德国几个高危群体以及非高危儿童的大规模纵向数据。.这些数据可以识别和比较目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，移民背景的儿童和有特殊教育需求（SEN）的学习者。此外，NEPS的大数据集允许用于分析测试项目的方法的改进。由于高危人群的人口统计学和其他差异，单个测试项目可能无法为高危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。 我们建议通过识别三个风险群体来解决这些问题，包括低SES，移民背景和NEPS数据集中有SEN的学习者，并通过数学，科学和拼写以及元认知能力纵向分析他们的发展。我们将使用一种新的差分项目功能（DIF）分析，以量化的程度，NEPS项目是不是在风险和非风险儿童不变。最后，使用合理的价值观，我们将产生定量的纵向发展模型，如潜在的增长，配置文件，并为两组的变化模型，以确定在风险学习者的弹性预测因素。 这项工作将有助于显着的弹性研究和项目反应理论（IRT）的方法，以及提供实用的指导研究人员使用包括在NEPS或类似的大规模研究中的量表比较的风险儿童与那些没有风险。

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.