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

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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.