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1.
Early childhood is a sensitive period for learning and social skill development. The maturation of cerebral regions underlying social processing lays the foundation for later social-emotional competence. This study explored myelin changes in social brain regions and their association with changes in parent-rated social-emotional development in a cohort of 129 children (64 females, 0–36 months, 77 White). Results reveal a steep increase in myelination throughout the social brain in the first 3 years of life that is significantly associated with social-emotional development scores. These findings add knowledge to the emerging picture of social brain development by describing neural underpinnings of human social behavior. They can contribute to identifying age-/stage-appropriate early life factors in this developmental domain.  相似文献   
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Research in Higher Education - Given the significant need to increase and diversify graduate enrollments within computing fields, it is vital to understand what shapes students’ pathways to...  相似文献   
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This self-reflexive activity acts as an introduction to how we talk about and express gender identity, as well as the assumptions we may have about gender identity norms and expression. The activity illuminates student’s subconscious behaviors and understandings of gender, pushing them to sit self-reflexively with their own understandings of gender as an identity, expression, binary, and potential locus of shame/freedom.

Courses: Introduction to Women and Gender Studies, Intercultural Communication, Media Studies, Gender and Communication, Performance Studies

Objectives: Designed to introduce students to their own understandings and embodiment of gender, this activity asks students to be honest about their preconceived notions regarding gender that they bring with them into the classroom. The activity utilizes predesigned components that test students’ subconscious knowledge of the gender binary. This is a one-time activity that can be conducted in one 50- or 75-minute class period.  相似文献   
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ABSTRACT

The aims of this study were to identify profiles of sedentary behaviour (SB) patterns, based on leisure-time self-reported SB modalities (screen, educative, social, and relaxing) and to evaluate changes in these profiles over 2 years among Spanish youth aged 8–18 years. Latent profile analysis (LPA), a data-driven analytic approach, was used to identify groups of boys and girls (n = 1553; 48% girls; mean±SD age: 12.56 ± 2.49 y) with distinct SB profiles using the SB modalities (time/d) as input variables. Latent transition analysis, an extension of LPA that uses longitudinal data, was used to analyse 2-year changes in these profiles. At baseline, four and three SB profiles were found among boys (labelled: screen, educative, social, and relaxing) and girls (labelled: screen/social, educative, and relaxing), respectively. Overall, more girls (range: 48%-67%) had the same profile over time, than boys (40%-52%). Participants with a screen or relaxing SB profile at baseline were more likely to have an educative profile after 2 years. Youth with a social and an educative SB profile at baseline were more likely to transition to profiles characterized by higher screen and social SB, respectively. Using a novel and person-centered approach, this study identified gender-specific SB profiles that were moderately stable over time.  相似文献   
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Cultural Studies of Science Education - The retention of underrepresented students remains a significant challenge in the STEM (Science, Technology, Engineering and Math) disciplines. A broad range...  相似文献   
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In this digital ITEMS module, Dr. Jeffrey Harring and Ms. Tessa Johnson introduce the linear mixed effects (LME) model as a flexible general framework for simultaneously modeling continuous repeated measures data with a scientifically defensible function that adequately summarizes both individual change as well as the average response. The module begins with a nontechnical overview of longitudinal data analyses drawing distinctions with cross-sectional analyses in terms of research questions to be addressed. Nuances of longitudinal designs, timing of measurements, and the real possibility of missing data are then discussed. The three interconnected components of the LME model—(1) a model for individual and mean response profiles, (2) a model to characterize the covariation among the time-specific residuals, and (3) a set of models that summarize the extent that individual coefficients vary—are discussed in the context of the set of activities comprising an analysis. Finally, they demonstrate how to estimate the linear mixed effects model within an open-source environment (R). The digital module contains sample R code, diagnostic quiz questions, hands-on activities in R, curated resources, and a glossary.  相似文献   
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