An Innovative Screener for Reading and SLI targeting Kindergarten through 3rd Grade Students

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As highlighted by the COVID-19 pandemic, there is a need for a usable online screener for children with language and reading disorders to support early reading instruction. In the absence of adequate screening, disorders are under-diagnosed and detected too late, resulting in adverse academic outcomes. While research shows that digital tools can successfully screen for language disorders such as SLI (Grammaggio), and reading disorders such as dyslexia (Amira Reading Screener), currently no practical, cost-effective and reliable screening method exists which integrates information about a child's language and reading skills. Our goal is to create a reliable & valid digital screening process amenable to implementation by schools. The goal is to identify at-risk children by combining the predictive role of language impairments (expressed via grammar) with a fully-automated early reading assessment (expressed via reading aloud). By directly comparing the results of both screeners, the research aims to establish the parameters for a unified screener able to operate within the critical constraints of usefulness, namely: modest test time to avoid lost instructional time; an extremely low false positive rate; minimal requirements for teacher training, and; easy access from both the classroom and home. One asset is a sample of children participating in an ongoing longitudinal study with well-documented diagnosis of SLI and reading disorders in addition to extensive experience with Grammaggio. The second asset is a well-documented innovative technology for teaching reading to children (Amira) coupled to a proven reading screener (Amira Reading Screener). Aim 1 is to determine if the combination of a language screener and a reading screener yields increased accuracy for identification of children with reading disorders. Aim 2 is to identify possible correspondences of reading errors identified by Amira with grammatical errors evaluated by Grammaggio. Four groups of children will be recruited from an existing longitudinal sample: SLI, reading disordered, both SLI and reading disorders, and control children. Screening outcomes will be validated against an external gold standard, the existing measurement protocol in R01DC001803 that provides standardized language and reading assessments of participating children. Successful completion of the aims will determine whether a combined electronic screener can reliably, validly, and cost-effectively flag students at-risk for specific disorders. Our prediction is that we will improve our understanding of the overlaps and interactions between reading and language disorders, leading to earlier and more effective treatments of these disorders. The team proposing this work benefits from the field expertise of Rice's team in ongoing data assessments and includes key personnel from Amira Learning. The combination of assets and expertise is well-positioned to make significant progress. Preliminary data collection in advance of this submission suggests that our integrated prototype screener will improve identification of children at-risk for language and reading disorders.