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1. What categorical induction variability reveals about typical and atypical development

   https://doi.org/10.1017/S0305000920000392  

   TECOULESCO, Lisa; FEIN, Deborah; NAIGLES, Letitia R. (May 2021, Journal of Child Language)

   null (Ed.)

   Abstract Categorical induction abilities are robust in typically developing (TD) preschoolers, while children with Autism Spectrum Disorders (ASD) frequently perform inconsistently on tasks asking for the transference of traits from a known category member to a new example based on shared category membership. Here, TD five-year-olds and six-year-olds with ASD participated in a categorical induction task; the TD children performed significantly better and more consistently than the children with ASD. Concurrent verbal and nonverbal tests were not significant correlates; however, the TD children's shape bias performance at two years of age was significantly positively predictive of categorical induction performance at age five. The shape bias, the tendency to extend a novel label to other objects of the same shape during word learning, appears linked with categorical induction ability in TD children, suggesting a common underlying skill and consistent developmental trajectory. Word learning and categorical induction appear uncoupled in children with ASD. 

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2. Preschool Data Scientists: Using a Digital Tool to Create Child-Centered Investigations

   https://doi.org/10.1080/00368148.2024.2340790  

   Lewis_Presser, Ashley; Young, Jessica Mercer (May 2024, Science and Children)

   NA (Ed.)

   This article describes the use of a digital tool to conduct investigations that allow young children to collect data to answer questions that are interesting and developmentally appropriate for preschoolers. The curricular program is designed as a set of hands-on experiences for preschoolers to engage in problem-solving with data. The digital tool supports the teacher to mediate each step in the investigation process, as preschoolers collaborate to pose a question of interest, identify categories or variables that can help answer the question, proceed through the data collection process, and quickly generate a visualization (graph or tally chart) that drives a deeper discussion or “data talk” to make sense of the data. By maximizing the affordances of technology, data can be efficiently collected while children engage in science practices (e.g. asking questions) and mathematics learning (e.g. gather relevant data, sort and classify by attributes, analysis and interpretation of data). The use of this digital resource amplifies the scaffolding of each investigation, assists in the details of planning and conducting investigations, and provides colorful, engaging visuals to spur discussions about the data in relevant, age-appropriate ways. Throughout the process, children can build on and expand their mathematics and scientific knowledge and skills. 

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3. Age‐related changes in information‐seeking behavior about morally relevant events

   https://doi.org/10.1111/cdev.14200  

   Yonas, Daniel; Solomon, Larisa Heiphetz (November 2024, Child Development)

   Abstract With age, people increasingly emphasize intent when judging transgressions. However, people often lack information about intent in everyday settings; further, they may wonder about reasons underlying pro‐social acts. Three studies investigated 4‐to‐6‐year‐olds', 7‐to‐9‐year‐olds', and adults' (data collected 2020–2022 in the northeastern United States, totaln = 669, ~50% female, predominantly White) desire for information about why behaviors occurred. In Study 1, older children and adults exhibited more curiosity about transgressions versus pro‐social behaviors (ds = 0.52–0.63). Younger children showed weaker preferences to learn about transgressions versus pro‐social behaviors than did older participants (d = 0.12). Older children's emphasis on intent, but not expectation violations, drove age‐related differences (Studies 2–3). Older children may target intent‐related judgments specifically toward transgressions, and doing so may underlie curiosity about wrongdoing. 

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4. The potential of data collection and analysis activities for preschoolers: A formative study with teachers

   https://doi.org/10.5121/ijite.2022.11101  

   Lewis Presser, A. E. (March 2022, International journal of integrating technology in education)

   To support preschool children’s learning about data in an applied way that allows children to leverage their existing mathematical knowledge (i.e. counting, sorting, classifying, comparing) and apply it to answering authentic, developmentally appropriate research questions with data. To accomplish this ultimate goal, a design-based research approach [1] was used to develop and test a classroom-based preschool intervention that includes hands-on, play-based investigations with a digital app that supports and scaffolds the investigation process for teachers and children. This formative study was part of a codesign process with teachers to elicit feedback on the extent to which the series of investigations focused on data collection and analysis (DCA) and the teacher-facing app were (a) developmentally appropriate, (b) aligned with current preschool curricula and routines, (c) feasible to implement, and (d) included design elements and technology affordances teachers felt were useful and anticipated to promote learning. Researchers conducted in-depth interviews (n=10) and an online survey (n=19) with preschool teachers. Findings suggest that teaching preschoolers how to collect and analyze data in a hands-on, play-based, and developmentally appropriate way is feasible and desirable for preschool teachers. Specifically, teachers reported that the initial conceptualization of the investigations were developmentally appropriate, aligned with existing curricular activities and goals, was adaptable for the age and developmental readiness of young children, and that the affordances of the technology are likely to allow preschool children to engage meaningfully in data collection, visualization, and analysis. Findings also suggest that this approach to supporting preschool teachers and children to learn about and conduct DCA merits further study to ensure productive curricular implementation that positively influences preschoolers’ learning. These findings were used to revise the investigations and app, which showed positive outcomes when used in classrooms [2], which add to the scant literature on DCA learning for pre-schoolers and provides insights into the best ways to integrate technology into the classroom. 

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5. Differences in the functional brain architecture of sustained attention and working memory in youth and adults

   https://doi.org/10.1371/journal.pbio.3001938  

   Kardan, Omid; Stier, Andrew J.; Cardenas-Iniguez, Carlos; Schertz, Kathryn E.; Pruin, Julia C.; Deng, Yuting; Chamberlain, Taylor; Meredith, Wesley J.; Zhang, Xihan; Bowman, Jillian E.; et al (December 2022, PLOS Biology)

   Cohen Kadosh, Roi (Ed.)

   Sustained attention (SA) and working memory (WM) are critical processes, but the brain networks supporting these abilities in development are unknown. We characterized the functional brain architecture of SA and WM in 9- to 11-year-old children and adults. First, we found that adult network predictors of SA generalized to predict individual differences and fluctuations in SA in youth. A WM model predicted WM performance both across and within children—and captured individual differences in later recognition memory—but underperformed in youth relative to adults. We next characterized functional connections differentially related to SA and WM in youth compared to adults. Results revealed 2 network configurations: a dominant architecture predicting performance in both age groups and a secondary architecture, more prominent for WM than SA, predicting performance in each age group differently. Thus, functional connectivity (FC) predicts SA and WM in youth, with networks predicting WM performance differing more between youths and adults than those predicting SA. 

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