Project II: Developing Dynamic Forecasting Intervention Algorithms for Children with Severe Literacy Disabilities

摘要 项目2 太多的孩子没有达到熟练的读写技能，这严重影响了公共卫生和 经济后果。这是因为读写困难与年级保持有关， 转介到特殊教育，高中辍学，进入少年刑事司法系统。 此外，平均而言，学习障碍学生的识字水平是一个标准偏差 低于一般发育阶段的学生，来自低社会经济背景的儿童实现 他们的识字水平低于他们的富裕同龄人。在NICHD和IES的资助下，我们已经取得了 通过使用动态预测在改善儿童识字成果方面取得了重要进展 教学评估(A2I)技术中的干预(DFI)算法。A2I是一种基于网络的教学 旨在提高教师个性化(或个性化)教学效率的支持技术 识字教学。然而，目前还不清楚A2i DFI算法预测最优数量和类型的准确性 为阅读和写作技能处于连续统一体中最底层的儿童提供指导，以及 最不可能对普通教育和密集干预措施作出反应。因此，总体目标是 建议的研究是利用我们在过去13年中开发DFI算法所学到的知识 和A2i，并进行随机对照试验，以测试它们的精密度和有效性；并解决 最严重学习障碍儿童的学习需求，包括阅读障碍和 书写困难。该项目有三个具体且相互关联的目标。目标1是确定，使用现有的 评估和观察数据，当前DFI算法对严重识字儿童的预测性 问题，阅读困难和书写困难；开发扩展的算法，包括发现的儿童特征 对于预测对干预和辅助干预等其他干预类型的反应很重要 技术；并模拟各种算法对学生在学年中的成绩的影响。 目标2是将扩展的DFI算法整合到A2I技术中，该技术将显示 对特定类型的指导/干预以及住宿和辅助设施的建议 技术目标3是进行一项前瞻性研究，以密切检查课堂的性质和可变性 为有严重识字障碍、阅读困难和书写困难的儿童提供指导。广泛实施，这些 研究有可能提高我们最脆弱的儿童的识字技能，这些儿童患有严重的 此外，他们还将继续努力解决学习障碍问题，并改善他们在学业和其他方面的生活质量。

ABSTRACT Project 2 Too many children fail to achieve proficient reading and writing skills, which has serious public health and economic consequences. This is because reading and writing difficulties are associated with grade retention, referral to special education, dropping out of high school, and entering the juvenile criminal justice system. Moreover, on average, the literacy proficiency of students with learning disabilities is one standard deviation lower than that of typically developing students, and children from low socio-economic backgrounds achieve lower literacy proficiency than their more affluent peers. With funding from NICHD and IES, we have made important strides in improving literacy outcomes for children through the use of dynamic forecasting intervention (DFI) algorithms in Assessment-to-instruction (A2i) technology. A2i is a web-based teaching support technology designed to improve teachers' effectiveness in delivering individualized (or personalized) literacy instruction. However, it is not clear how well the A2i DFI algorithms predict optimal amounts and types of instruction for children whose reading and writing skills fall at the lowest tail of the continuum, and who are least likely to be responsive to general education and intensive interventions. Hence, the overarching aim of the proposed research is to use what we have learned over the past 13 years of developing the DFI algorithms and A2i and conducting randomized controlled trials to test their precision and efficacy; and to address the learning needs of children with the most severe learning disabilities including those with dyslexia and dysgraphia. The project has three specific and interrelated aims. Aim 1 is to determine, using extant assessment and observation data, how predictive current DFI algorithms are for children with severe literacy problems, dyslexia, and dysgraphia; develop expanded algorithms that include child characteristics found to be important for the prediction of response to intervention and additional types of intervention such as assistive technologies; and run simulations of the impact of various algorithms on students' gains during the school year. Aim 2 is to incorporate the expanded DFI algorithms into the A2i technology, which will display recommendations for specific types of instruction/intervention as well as accommodations and assistive technology. Aim 3 is to conduct a prospective study to closely examine the nature and variability of classroom instruction for children with severe literacy disabilities, dyslexia, and dysgraphia. Broadly implemented, these studies have the potential to improve the literacy skills of our most vulnerable children, those with severe learning disabilities, and to improve the quality of their lives academically and beyond.