Investigating Children's Interactions in Preschool Classrooms: An Overview of Research Using Automated Sensing Technologies.

New technologies that combine digital sensors with automated processing algorithms are now being deployed to study preschool classrooms. This article provides an overview of these new sensing technologies, focusing on automated speaker classification, the analysis of children's and teachers' speech, and the detection and analysis of their movements over the course of the school day. Findings from recent studies utilizing these technologies are presented to illustrate the contribution of these sensing technologies to our understanding of classroom processes that predict children's language and social development. In particular, the potential to collect extended real-time data on the speech and movement of all children and teachers in a classroom provides a broader window on the variability of individual children's interactions with peers and teachers and their integration into classroom social networks. The article describes current challenges related to the use of sensing technologies in preschool settings, as well as advances that may overcome these challenges and allow for more in-depth investigations of children's early classroom experiences.

Objectively measured teacher and preschooler vocalizations: Phonemic diversity is associated with language abilities.

Over half of US children are enrolled in preschools, where the quantity and quality of language input from teachers are likely to affect children's language development. Leveraging repeated objective measurements, we examined the rate per minute and phonemic diversity of child and teacher speech-related vocalizations in preschool classrooms and their association with children's end-of-year receptive and expressive language abilities measured with the Preschool Language Scales (PLS-5). Phonemic diversity was computed as the number of unique consonants and vowels in a speech-related vocalization. We observed three successive cohorts of 2.5-3.5-year-old children enrolled in an oral language classroom that included children with and without hearing loss (N = 29, 16 girls, 14 Hispanic). Vocalization data were collected using child-worn audio recorders over 34 observations spanning three successive school years, yielding 21.53 mean hours of audio recording per child. The rate of teacher vocalizations positively predicted the rate of children's speech-related vocalizations while the phonemic diversity of teacher vocalizations positively predicted the phonemic diversity of children's speech-related vocalizations. The phonemic diversity of children's speech-related vocalizations was a stronger predictor of end-of-year language abilities than the rate of children's speech-related vocalizations. Mediation analyses indicated that the phonemic diversity of teacher vocalizations was associated with children's receptive and expressive language abilities to the extent that it influenced the phonemic diversity of children's own speech-related vocalizations. The results suggest that qualitatively richer language input expands the phonemic diversity of children's speech, which in turn is associated with language abilities.

A mixed methods, cluster randomized control trial to examine assistive technology use to support early literacy in preschool children with disabilities.

This mixed methods study examined the impact of a multi-faceted professional development (PD) program for preschool teachers and classroom assistants on teacher-supported assistive technology (AT) use and early literacy development of children with disabilities. Four special education preschools were randomized into intervention (2 schools, 9 teachers, 50 children) and waitlist control (2 schools, 17 teachers, 42 children) groups. The 24-week PD included online modules, coaching, and AT device kits. Pre-post gains in children's AT use and early literacy skills were analyzed using χ2 and repeated measures ANOVA. Teacher interviews and reflective commentaries were analyzed using Framework Analysis methodology. From pre- to post-test, the percent of children in the intervention group using some form of AT rose from 36 to 80%. The percent of children using AT in the control group went from 45 to 62%. The difference in change between the two groups was statistically significant, χ2 = 13.93, p=.001. Gains in early literacy skills were not significantly different across groups, F(1,90)=0.010, p=.922. Analysis of the qualitative data revealed three themes: the positive impact of AT on child engagement and participation, the importance of individualizing AT for each student, and barriers teachers faced in AT implementation. The PD program had a positive effect on children's AT use but not on gains in early literacy. Teachers' comments highlighted the nuanced relationship between AT use and literacy outcomes, suggesting the need for more targeted implementation of AT during literacy activities.

This research emphasized the importance of a comprehensive approach to PD that involves hands-on AT experience and coaching to bolster the AT practices of early childhood educators.The multi-faceted PD provided to preschool staff increased children's teacher-supported AT use but was not shown to result in increased gains in early literacy skills. These results highlight the need for additional focused research to elucidate how to best leverage AT to advance foundational early literacy competencies.Professional development that trains teachers and classroom assistants collaboratively as a unit promotes inclusive, empowered implementation and allows for integrated AT planning that utilizes assistants' expanding roles vis-á-vis students with disabilities.Future research should investigate flexible coaching approaches, just-in-time learning, and train-the-trainer models that cultivate site-based AT expertise and on demand resources to provide ongoing, tailored support and build local capacity, promoting sustainability and mitigating barriers like time constraints and high teacher turnover.

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.

Construction and validation of two parent-report scales for the evaluation of early intervention programs.

The State Performance Plan (SPP) developed under the 2004 reauthorization of the Individuals with Disabilities Education Act (IDEA 2004, Public Law 108-446) requires states to collect data and report on the impact of early intervention services on three key outcomes for participating families. The NCSEAM Impact on Family Scale (NIFS) and the NCSEAM Family Centered Services Scale (NFCSS) were developed to provide states with a means to address this new reporting requirement and to collect additional data that would inform program improvement efforts. Items suggested by stakeholder groups were piloted with a nationally representative sample of parents of children with developmental delays or disabilities ages birth to three participating in early intervention services in eight states. The 28-item NIFS had measurement reliabilities ranging from .93-.96 in a sample of 1,750; measurement reliabilities for the 135-item NFCSS ranged from .94 to .97 in a sample of 1,755 respondents. A 29-item version of the NFCSS had measurement reliabilities ranging from .87 to .92. Using data from the pilot study, stakeholders established a recommended performance standard, set at a meaningful point in the NIFS item hierarchy, for each of the three established outcome areas.

Measuring schools' efforts to partner with parents of children served under IDEA: scaling and standard setting for accountability reporting.

Indicator 8 of the State Performance Plan (SPP), developed under the 2004 reauthorization of the Individuals with Disabilities Education Act (IDEA 2004, Public Law 108-446) requires states to collect data and report findings related to schools' facilitation of parent involvement. The Schools' Efforts to Partner with Parents Scale (SEPPS) was developed to provide states with a means to address this new reporting requirement. Items suggested by stakeholder groups were piloted with a nationally representative sample of 2,634 parents of students with disabilities ages 5-21 in six states. Rasch scaling was used to calibrate a meaningful and invariant item hierarchy. The 78 calibrated items had measurement reliabilities ranging from .94-.97. Using data from the pilot study, stakeholders established a recommended performance standard set at a meaningful point in the item hierarchy. Implications of the findings are discussed in relation to the need for rigorous metrics within state accountability systems.

Empirically Identified Subgroups of Children Served in Part C Early Intervention Programs.

OBJECTIVE: Early intervention (EI) programs under Part C of the Individuals with Disabilities Education Act serve a developmentally heterogeneous population of infants and toddlers with or at risk of developmental delays or disabilities. The aim of this study was to identify empirically distinct subgroups of children in EI so as to inform early prognosis and service planning. METHODS: We applied mixture modeling to developmental assessment data from 1513 children who enrolled in a large, urban EI program between 2009 and 2013. The observed variables were children's EI-entry developmental quotients (DQs) in 5 domains (communication, cognitive, motor, adaptive, and personal-social) as assessed by the Battelle Developmental Inventory, Second Edition. RESULTS: A 4-class model showed the best fit to the data, revealing subgroups with distinct developmental profiles. Children in the first subgroup showed a severe delay in communication with less severe delays in the other domains. Children in the second subgroup likewise showed a severe delay in communication, but with comparably severe delays in the cognitive and motor domains. Profiles for the third and fourth subgroups showed the same overall patterns as those for the first and second subgroups, respectively, but to a less severe degree. Developmental trajectories differed by subgroup. CONCLUSION: Consideration of subgroups based on children's developmental assessment scores provides insight into underlying commonalities among children with different presenting diagnoses on entry into EI. The subgroups also have clinical relevance in terms of both practitioners' and parents' understanding of children's likely service needs and developmental trajectories.

For which students with learning disabilities are self-concept interventions effective?

We have previously conducted a meta-analysis of outcomes of school-based interventions aimed at enhancing the self-concept of students with learning disabilities (LD). This study extends the previous findings by analyzing intervention effect sizes in relation to students' levels of self-concept prior to intervention. The results of these analyses indicated that only groups of students with documented low self-concept benefited significantly from intervention. For these students, intervention effects were much larger than the effects previously estimated from aggregations that included groups with wide-ranging or unknown levels of self-concept prior to intervention. These findings underscore the need for researchers and practitioners to identify students for self-concept intervention based on their documented need, rather than assuming a need based on the students' identification as students with LD.