Complex cognitive processes, like creative thinking, rely on interactions among multiple neurocognitive processes to generate effective and innovative behaviors on demand, for which the brain’s connector hubs play a crucial role. However, the unique contribution of specific hub sets to creative thinking is unknown. Employing three functional magnetic resonance imaging datasets (total N= 1,911), we demonstrate that connector hub sets are organized in a hierarchical manner based on diversity, with “control-default hubs”—which combine regions from the frontoparietal control and default mode networks—positioned at the apex. Specifically, control-default hubs exhibit the most diverse resting-state connectivity profiles and play the most substantial role in facilitating interactions between regions with dissimilar neurocognitive functions, a phenomenon we refer to as “diverse functional interaction”. Critically, we found that the involvement of control-default hubs in facilitating diverse functional interaction robustly relates to creativity, explaining both task-induced functional connectivity changes and individual creative performance. Our findings suggest that control-default hubs drive diverse functional interaction in the brain, enabling complex cognition, including creative thinking. We thus uncover a biologically plausible explanation that further elucidates the widely reported contributions of certain frontoparietal control and default mode network regions in creativity studies. © The Author(s) 2023. Published by Oxford University Press. All rights reserved.

Teachers' mathematical knowledge has important consequences for the quality of the learning environment they create for their students to learn mathematics. Yet relatively little is known about how teachers reason proportionally, despite the fact that proportional reasoning is foundational for several mathematics concepts and that ratios and proportional relationships constitute a major component of the middle school mathematics curriculum. In this study, we investigated how teachers reasoned proportionally on a nonroutine ratio task and the extent to which their proportional reasoning was able to predict their overall understanding of the relevant concepts: ratios and proportional relationships. Using data collected from 238 US mathematics teachers, we found that teachers' proportional reasoning could be grouped into four categories: incorrect, additive, relative, and proportional reasoning. Our results also indicated that teachers' overall knowledge of ratios and proportional relationships aligned with the way they reasoned proportionally, meaning that teachers who used incorrect reasoning on a separate task received the lowest scores on average on the ratios and proportional relationships measure, whereas those who reasoned proportionally had the highest mean scores on average. Implications of the study include the need to shift attention to the way teachers reason in relation to the two elements of proportional reasoning (covariance and invariance) to capture the nuances in their understanding of ratios and proportional relationships.

Teachers' knowledge of students' mathematical thinking is a growing area of research in mathematics education. The literature has reported plentiful evidence of the interplays between teachers' mathematical knowledge and their knowledge of students' mathematical thinking. The present study builds on this body of work to explain how such interplays occur. Over a semester, I worked in partnership with a secondary school mathematics teacher on cycles of task design, interactions with a student, and in-depth reflection on the student's thinking about linear programming. Adopting and extending Piagetian constructs of assimilation and accommodation, I describe several key mental processes that illuminate the teacher's learning of mathematics and of the student's mathematical thinking. I conclude with a discussion of the study's empirical and theoretical contributions to understanding teachers' mathematical learning in relation to student thinking.

Multi-modal approaches in engineering and computing education are still in its early stages. With the advent of new technologies and communication platforms, understanding the principles and elements of multi-modal work will help scholars to answer complex research questions related to engineering and computing education. Multi-modal approaches consist of research principles and practices that aim to explore the multi-sensory ways humans experience the complexity and multiplicity of their surrounding world as it happens. This manuscript will elaborate on the principles of multi-modal research, highlight examples in the engineering and computing education literature, and share considerations and strategies. The manuscript’s purpose is to guide scholars who wish to capture participant experiences of phenomena naturalistically and authentically, and in near-real-time. © 2023 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

Music is a complex system consisting of many dimensions and hierarchically organized information-the or-ganization of which, to date, we do not fully understand. Network science provides a powerful approach to representing such complex systems, from the social networks of people to modelling the underlying network structures of different cognitive mechanisms. In the present research, we explored whether network science methodology can be extended to model the melodic patterns underlying expert improvised music. Using a large corpus of transcribed improvisations, we constructed a network model in which 5-pitch sequences were linked depending on consecutive occurrences, constituting 116,403 nodes (sequences) and 157,429 edges connecting them. We then investigated whether mathematical graph modelling relates to musical characteristics in real -world listening situations via a behavioral experiment paralleling those used to examine language. We found that as melodic distance within the network increased, participants judged melodic sequences as less related. Moreover, the relationship between distance and reaction time (RT) judgements was quadratic: participants slowed in RT up to distance four, then accelerated; a parallel finding to research in language networks. This study offers insights into the hidden network structure of improvised tonal music and suggests that humans are sen-sitive to the property of melodic distance in this network. More generally, our work demonstrates the similarity between music and language as complex systems, and how network science methods can be used to quantify different aspects of its complexity.

People often self-identify as allies to the lesbian, gay, bisexual, and transgender (LGBT) community. This research examined on what basis LGBT individuals perceive others to be allies and documents the consequences of perceived allyship. Studies 1a (n = 40) and 1b (n = 69) collected open-ended descriptions of allyship provided by LGBT participants. Coding of the responses suggested multiple components to being an ally: (a) being nonprejudiced toward the group, (b) taking action against discrimination and inequality, and (c) having humility about one’s perspective in discussions about LGBT issues. In Studies 2a (n = 161) and 2b (n = 319, with nationally representative characteristics), an allyship scale was developed and validated for general and specific relational contexts, respectively. Study 2b also showed that LGBT individuals’ perceptions of close others’ allyship were positively associated with their own well-being and relationship quality with the close other. Study 3, an experiment, demonstrated that nonprejudice and action had an interactive effect on perceived allyship, such that action increased perceived allyship more when prejudice was low (vs. high). Study 4 was a weekly experience study of LGBT participants and an outgroup roommate. Perceiving one’s roommate to be a good ally predicted higher self-esteem, greater subjective well-being, and better relationship quality with the roommate, both between and within participants. Furthermore, perceived allyship in 1 week was associated with increases in LGBT individuals’ mental health and relationship quality with the roommate the following week. This research advances knowledge about what allyship means to LGBT individuals and identifies intra-and interpersonal benefits of allyship. © 2023 American Psychological Association

Objective COVID-19 has presented threats to adolescents' psychosocial well-being, especially for those from economically disadvantaged backgrounds. This longitudinal study aimed to identify which social (i.e., family conflict, parental social support, peer social support), emotional (i.e., COVID-19 health-related stress), and physical (i.e., sleep quality, food security) factors influence adolescents' same- and next-day affect and misconduct and whether these factors functioned differently by adolescents' economic status. Method Daily-diary approaches were used to collect 12,033 assessments over 29 days from a nationwide sample of American adolescents (n =546; M-age = 15.0; 40% male; 43% Black, 37% White, 10% Latinx, 8% Asian American, and 3% Native American; 61% low-income) at the onset of the COVID-19 pandemic. Results Peer support, parent support, and sleep quality operated as promotive factors, whereas parent-child conflict and COVID-19 health-related stress operated as risk factors. Although these links were consistent for adolescents irrespective of economic status, low-income adolescents experienced more conflict with parents, more COVID-19 health-related stress, less peer support, and lower sleep quality than higher-income adolescents. Food insecurity was connected to decreased same- and next-day negative affect for low-income adolescents only. Low-income adolescents also displayed greater negative affect in response to increased daily health-related stress relative to higher-income adolescents. Conclusion These results highlight the role of proximal processes in shaping adolescent adjustment and delineate key factors influencing youth psychosocial well-being in the context of COVID-19. By understanding adolescents' responses to stressors at the onset of the pandemic, practitioners and healthcare providers can make evidence-based decisions regarding clinical treatment and intervention planning for youth most at risk for developmental maladjustment.

There is a long-standing interest in the role that children's understanding of pretense plays in their more general theory of mind development. Some argue that children understand pretense as a mental state, and the capacity to pretend is indicative of children possessing the capacity for mental representations. Others argue that children understand pretense in terms of actions and appearances, and an understanding of the mental states involved in pretending has a prolonged developmental trajectory. The goal of this paper is to integrate these ideas by positing that children understand pretense as a form of causal inference, which is based on both their general causal reasoning capacities and specific knowledge of mental states. I will first review literature on children's understanding of pretense, and how such understanding can be conceptualized as integrating with children's causal reasoning ability. I will then consider how children's causal knowledge affects the ways they make inferences about others' pretense. Next, I will consider the role of causal knowledge more broadly in children's reasoning about pretense worlds, judgments of possibility, and counterfactual reasoning. Taken together the goal of this review is to synthesize how children understand pretending into a rational constructivist framework for understanding social cognitive development in a more integrative manner.

Many STEM degree holders, especially women and minorities, are not employed in STEM occupations in the United States, and transitions into the STEM labor force among recent graduates have been declining since the 1980 ' s. We examine transitions from school to work at two large U.S. universities in 2015-16, focusing on the internship experiences and job search strategies of graduating chemistry and chemical engineering majors. Surprisingly, 28% of our STEM respondents had no post-graduation plans, though women were significantly more likely than men to already have a job. Overall race differences in post-graduation plans were insignificant, though Black and Hispanic students were more likely to have no post-graduation plans compared to Whites and Asians. While Black, Hispanic, and LGBT students reported fewer job search behaviors overall, potentially explaining this pattern, no gender differences in job search behaviors or internship experiences emerged to explain women's employment advantage. However, better grades led to early job offers, reducing most of women's initial hiring advantage along with positive internship experiences, which did not alter men's likeli-hood of a job offer but were associated with a higher likelihood of a job offer among women.

Learning sciences are embracing the significant role technologies can play to better detect, diagnose, and act upon self-regulated learning (SRL). The field of SRL is challenged with the measurement of SRL processes to advance our understanding of how multimodal data can unobtrusively capture learners' cognitive, metacognitive, affective, and motivational states over time, tasks, domains, and contexts. This paper introduces a self-regulated learning processes, multimodal data, and analysis (SMA) grid and maps joint and individual research of the authors (63 papers) over the last five years onto the grid. This shows how multimodal data streams were used to investigate SRL processes. The two-dimensional space on the SMA grid is helpful for visualizing the relations and possible combinations between the data streams and how the measurement of SRL processes. This overview serves as an analytical introduction to the current special issue “Advancing SRL Research with Artificial Intelligence (AI)” and we encourage to position new research and unexplored frontiers. We emphasize the need for intensive and strategic collaboration to accelerate progress using new interdisciplinary methods to develop accurate measurement of SRL in educational technologies. © 2022 The Authors