Tiny Wearable Sensors Reveal Hidden Social Lives of Preschoolers Facing Behavioral Challenges

A preschooler’s social life can be remarkably difficult to see. In a busy inclusive classroom, a teacher responsible for sixteen four-year-olds cannot possibly track who plays with whom, for how long, and who walks away first—yet those details may matter enormously for children whose development depends on meaningful peer connection. A new exploratory study published in the Early Childhood Education Journal suggests that a lightweight wearable sensor system can capture exactly these invisible patterns, offering teachers objective data on the social engagement of children with behavioral challenges and language differences.

The study, conducted by researchers at Michigan State University including Kang Gao, Chandani Bhandari, Tianxiang Zhang, Sarah N. Douglas, and Subir Biswas, focused on a single target child in an inclusive preschool classroom who had been identified by his head teacher as facing both behavioral challenges and English language learner (ELL) status. The child, given the pseudonym Doruk, was a four-year-nine-month-old White male who spoke Turkish at home and used conversational English at school. His teacher reported that he engaged with peers in aggressive ways, such as hitting and biting, and that classmates had begun avoiding him as a result. Despite concerns shared with the family, no special education services were pursued, and Doruk carried no formal diagnosis related to his behavior.

The stakes of such early social difficulties are considerable. The authors note that nearly 22 percent of young children in the United States speak a language other than English at home, with 15 percent of kindergarten children identified as English language learners, while behavioral challenges affect approximately 14 percent of children in early childhood. Prior research has shown that children with behavioral challenges tend to engage in fewer peer interactions, are often excluded from peer play, experience more peer conflicts, have fewer friends, and more frequently play alone. For children who are ELL, peer interactions are often short-lived, and a lack of English proficiency can itself produce challenging behaviors when peers fail to understand a child’s messages—sometimes leading to special education referrals or exclusionary discipline.

The theoretical grounding for the work draws on complementary frameworks. Social engagement theory holds that active participation in social settings benefits both the child and peers, while a lack of engagement is associated with poorer mental health and behavioral difficulties. Vygotsky’s sociocultural theory emphasizes that peer interaction is crucial for cognitive and language development, and Bandura’s social learning theory highlights how children learn by observing and imitating their social environment—processes that can be hampered when language barriers exist. Together, these perspectives suggest that children with behavioral and language challenges may need additional, well-timed teacher support to build sustainable social engagement in preschool settings.

Measuring that engagement, however, has long been a practical bottleneck. Continuous observation is time-consuming, can introduce bias, and reduces the direct teaching time teachers have available. When teachers lack dedicated observation time, they may rely on memory, which the researchers note can be inaccurate. The study therefore employed the Wearable Human Interaction Tracker, or WHIT, a sensor system built around Ultra-Wideband (UWB) radio-based location tracking, integrating localization hardware from Eliko Systems within a custom wearable package. UWB localization was chosen because its performance has been validated in prior research and industrial applications.

The technical architecture of WHIT is elegantly simple in concept. Participants carry tag sensors that transmit UWB blink messages received by wall-mounted anchor sensors; using signal timing, the system performs triangulation to determine each child’s precise real-time location, forwarding computed positions to wall-mounted receiver sensors. Each sensor is the size of a standard credit card, weighs 12 grams, and carries a rechargeable battery lasting seven hours per charge. The electronics are sealed in plastic packaging for safety and secured with snaps into pockets of custom-made t-shirts to prevent removal. Doruk wore two sensors, one in each sleeve pocket, to detect the directionality of his movements, while his five participating peers wore a single front-pocket sensor each.

Proximity served as the indicator of social engagement. A threshold of one meter was chosen empirically based on prior studies: proximity within one meter maintained for at least 15 seconds was coded as social engagement, ending only when the distance exceeded one meter for 10 seconds or more—an approach that accommodated natural movement while preserving measurement accuracy. Calibration preceded data collection, and at least two research assistants independently logged each child’s location and behaviors every minute from an observation booth to validate the sensor data. Agreement between observational and sensor data reached 93.73 percent, with most disagreements occurring during transitions between classroom locations or near zone boundaries. Data were collected across six observation days over two months in late Fall 2024, during both structured teacher-led activities and unstructured free play, with sessions averaging 80 minutes.

The results painted a nuanced and somewhat surprising portrait of Doruk’s social world. His overall social connectivity was 45.1 percent, actually higher than the average of his peers, yet his average connectivity duration was shorter at 48.5 seconds compared with the peer average of 54.4 seconds. His connectivity with any individual peer never exceeded 19 percent, and he showed a preference for one peer, Otto, over the other four. The most striking finding emerged when activity type was considered: during structured, teacher-guided activities, Doruk’s social connectivity soared to 91.6 percent, exceeding every peer, while during unstructured free play it fell to 33.7 percent—the largest structured-versus-unstructured gap of any child in the study.

Initiation and termination data added another layer of insight. Doruk’s initiation rate was 53.1 percent, slightly above the peer average, and his initiation-to-termination ratio of 1.09 exceeded the classroom average of 0.97. In practical terms, Doruk frequently started social interactions, but it was usually his peers who ended them—a pattern the authors interpret as a less stable social engagement style, with limited peer interest in sustaining interactions. A spatial heatmap of his movements revealed a strong preference for the area between the kitchen and the center table, along with time spent at the craft and sensory tables, and comparatively little time in the book nook, animals, and blocks areas.

For the researchers, these findings carry clear implications for practice. The data suggest that Doruk may have a strong need for structure in his social interactions, and that teacher guidance allows him to engage more appropriately—while also indicating he may need support learning to sustain peer engagement and build stronger individual relationships. Teachers could use initiation and termination data to design interventions promoting meaningful peer interaction, scaffold social engagement activities strategically, and leverage area preferences when planning targeted activities. More broadly, the study demonstrated that individual differences in social connectivity, peer preference, and engagement patterns are common even among children without identified challenges—differences that continuous observation alone would rarely detect. The authors acknowledge limitations, including the single-classroom exploratory design, the inability to separate the effects of ELL status from behavioral challenges, and the asymmetric sensor configuration, and they call for larger samples and two-sensor configurations for all participants. With further development, they conclude, wearable sensor systems like WHIT could provide the objective, real-time data teachers need to complement their own observations and inform targeted interventions in inclusive preschool classrooms.

Subject of Research: Wearable sensor-based measurement of social engagement patterns in preschool children with behavioral challenges and English language learner status

Article Title: Sensor Technology to Measure Social Engagement for Children with Behavioral Challenges

Article References: Gao, K., Bhandari, C., Zhang, T., Douglas, S. N., & Biswas, S. (2026). Sensor Technology to Measure Social Engagement for Children with Behavioral Challenges. Early Childhood Education Journal. https://doi.org/10.1007/s10643-026-02353-y

Image Credits: AI Generated

DOI: 10.1007/s10643-026-02353-y

Keywords: wearable sensors, social engagement, preschool, behavioral challenges, English language learners, ultra-wideband localization, inclusive classrooms, early childhood education, peer interaction, child development, WHIT sensor system, teacher intervention