The Social Feedback Hypothesis and Communicative Development in Autism Spectrum Disorder: A Response to Akhtar, Jaswal, Dinishak, and Stephan (2016)

Putting the child in the driver's seat: Insights into language development from children's interactions in preschool classrooms

Children's own language production has a role in structuring the language of their conversation partners and influences their own development. Children's active participation in their own language development is most apparent in the rich body of work investigating language in natural environments. The advent of automated measures of vocalizations and movement have made such in situ research increasingly feasible. In this chapter, we review recent research on children's language development in context with a particular focus on research employing automated methods in preschool classrooms for children between ages 2 and 5 years. These automated methods indicate that the speech directed to preschool children from specific peers predicts the child's speech to those peers on a subsequent observation occasion. Similar patterns are seen in the influence of peer and teacher phonemic diversity on the phonemic diversity of children's speech to those partners. In both cases, children's own speech to partners was the best predictor of their language abilities, suggesting their active role in their own development. Finally, new research suggests the potential of machine learning to predict children's speech in group contexts, and to transcribe classroom speech to better understand the content of children's conversations and how they change with development.

Clinician Proposed Predictors of Spoken Language Outcomes for Minimally Verbal Children with Autism Spectrum Disorder

Our aim was to explore insights from clinical practice that may inform efforts to understand and account for factors that predict spoken language outcomes for children with Autism Spectrum Disorder who use minimal verbal language. We used a qualitative design involving three focus groups with 14 speech pathologists to explore their views and experiences. Using the Framework Method of analysis, we identified 9 themes accounting for 183 different participant references to potential factors. Participants highlighted the relevance of clusters of fine-grained social, communication, and learning behaviours, including novel insights into prelinguistic vocal behaviours. The participants suggested the potential value of dynamic assessment in predicting spoken language outcomes. The findings can inform efforts to developing clinically relevant methods for predicting children's communication outcomes.