ArticleEarly childhood research quarterly
Investigating Children's Interactions in Preschool Classrooms: An Overview of Research Using Automated Sensing Technologies.
Article in Early childhood research quarterly. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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Who cites it
4 citing papers in PubMed.
- Linking temporal dynamics of children's natural behavior to brain development.Developmental cognitive neuroscience · 2026Article
- The Use of Automated Digital Data in Speech, Language, and Hearing Research: Confronting a New Ethical Landscape.Journal of speech, language, and hearing research : JSLHR · 2025Article
- A Systematic Review of Modern Measures for Capturing Children's Ethnic and Racial Attitudes, Stereotypes, and Discrimination.Developmental review : DR · 2025Article
- Children's social preference for teachers versus peers in autism inclusion classrooms: An objective perspective.Autism research : official journal of the International Society for Autism Research · 2025Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
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.
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Registered trials
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