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1. Sociotechnical Design Opportunities for Pervasive Family Sleep Technologies

   https://doi.org/10.1145/3421937.3421979  

   Cherenshchykova, Anna; Miller, Andrew D. (May 2020, 14th EAI International Conference on Pervasive Computing Technologies for Healthcare (PervasiveHealth ’20))

   null (Ed.)

   Getting the right amount of high quality sleep is crucial for overall health and wellbeing, and pervasive and ubiquitous computing technologies have shown promise for allowing individuals to track and manage their sleep quality. However, sleep technology research has traditionally focused on individual-level solutions. In this paper, we elucidate social requirements for family sleep technologies. We take a family informatics approach to sleep, through an in-home interview study with 10 families with young children. We describe families’ current practices, values, and perceived role for technology, showing that sleep technology has many opportunities beyond individual-level tracking. We also provide design dimensions and implications for family-based sleep technologies, especially the potential for technologies that support family activities and rituals, encourage children’s independence, and provide comfort. 

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2. The technical matters: young children debugging (with) tangible coding toys

   https://doi.org/10.1108/ILS-12-2021-0109  

   Silvis, Deborah; Lee, Victor R.; Clarke-Midura, Jody; Shumway, Jessica F. (July 2022, Information and Learning Sciences)

   Purpose Much remains unknown about how young children orient to computational objects and how we as learning scientists can orient to young children as computational thinkers. While some research exists on how children learn programming, very little has been written about how they learn the technical skills needed to operate technologies or to fix breakdowns that occur in the code or the machine. The purpose of this study is to explore how children perform technical knowledge in tangible programming environments. Design/methodology/approach The current study examines the organization of young children’s technical knowledge in the context of a design-based study of Kindergarteners learning to code using robot coding toys, where groups of children collaboratively debugged programs. The authors conducted iterative rounds of qualitative coding of video recordings in kindergarten classrooms and interaction analysis of children using coding robots. Findings The authors found that as children repaired bugs at the level of the program and at the level of the physical apparatus, they were performing essential technical knowledge; the authors focus on how demonstrating technical knowledge was organized pedagogically and collectively achieved. Originality/value Drawing broadly from studies of the social organization of technical work in professional settings, we argue that technical knowledge is easy to overlook but essential for learning to repair programs. The authors suggest how tangible programming environments represent pedagogically important contexts for dis-embedding young children’s essential technical knowledge from the more abstract knowledge of programming. 

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3. Children’s Estimation of Peripheral Information Drives Improvements in Approximate Number Sense

   Yang, Huiwen Alex; Kidd, C; Piantadosi, S (June 2023, Proceedings of the Cognitive Science Society)

   Children rely on their approximate number system (ANS) to guess quantities from a young age. Studies have shown that older children displayed better ANS performance. However, previous research did not provide an explanation for this ANS improvement. We show that children’s development in ANS is primarily driven by improved attentional control and awareness of peripheral information. Children guess the number of dots on a computer screen while being eye-tracked in our experiment. The behavioral and eye-tracking results provide supporting evidence for our account. Our analysis shows that children estimate better under the longer display-time condition and more visual foveation, with the effect of visual foveation mediating that of time. It also shows that older children make fewer underestimations because they are better at directing their attention and gaze toward areas of interest, and they are also more aware of dots in their peripheral vision. Our finding suggests that the development of children’s ANS is significantly impacted by the development of children’s nonnumerical cognitive abilities. 

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4. Transitioning Toward Independence: Enhancing Collaborative Self-Management of Children with Type 1 Diabetes

   https://doi.org/10.1145/3491102.3502055  

   Cha, Yoon Jeong; Saxena, Arpita; Wou, Alice; Lee, Joyce; Newman, Mark W; Park, Sun Young (April 2023, the ACM/SIGCHI Conference on Human Factors in Computing Systems (CHI 2022))

   Although child participation is required for successful Type 1 Diabetes (T1D) management, it is challenging because the child’s young age and immaturity make it difficult to perform self-care. Thus, parental caregivers are expected to be heavily involved in their child’s everyday illness management. Our study aims to investigate how children and parents collaborate to manage T1D and examine how the children become more independent in their self-management through the support of their parents. Through semi-structured interviews with children with T1D and their parents (N=41), our study showed that children’s knowledge of illness management and motivation for self-care were crucial for their transition towards independence. Based on these two factors, we identified four types of children’s collaboration (i.e., dependent, resistant, eager, and independent) and parents’ strategies for supporting their children’s independence. We suggest design implications for technologies to support collaborative care by improving children’s transition to independent illness management. 

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5. Investigating children’s interactions in preschool classrooms: An overview of research using automated sensing technologies

   Elbaum, Batya; Perry, Lynn; Messinger, Daniel (October 2023, Early Childhood Research Quarterly)

   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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