Research in both laboratory and museum settings suggests that children’s exploration and caregiver–child interaction relate to children’s learning and engagement. Most of this work, however, takes a third-person perspective on children’s exploration of a single activity or exhibit, and does not consider children’s perspectives on their own exploration. In contrast, the current study recruited 6-to 10-year-olds (N = 52) to wear GoPro cameras, which recorded their first-person perspectives as they explored a dinosaur exhibition in a natural history museum. During a 10-min period, children were allowed to interact with 34 different exhibits, their caregivers and families, and museum staff however they wished. Following their exploration, children were asked to reflect on their exploration while watching the video they created and to report on whether they had learned anything. Children were rated as more engaged when they explored collaboratively with their caregivers. Children were more likely to report that they learned something when they were more engaged, and when they spent more time at exhibits that presented information didactically rather than being interactive. These results suggest that static exhibits have an important role to play in fostering learning experiences in museums, potentially because such exhibits allow for more caregiver–child interaction. Copyright © 2023 Weisberg, Dunlap and Sobel.

Meta-analysts often ask a yes-or-no question: Is there an intervention effect or not? This traditional, all-or-nothing thinking stands in contrast with current best practice in meta-analysis, which calls for a heterogeneity-attuned approach (i.e., focused on the extent to which effects vary across procedures, participant groups, or contexts). This heterogeneity-attuned approach allows researchers to understand where effects are weaker or stronger and reveals mechanisms. The current article builds on a rare opportunity to compare two recent meta-analyses that examined the same literature (growth mindset interventions) but used different methods and reached different conclusions. One meta-analysis used a traditional approach (Macnamara & Burgoyne, 2023), which aggregated effect sizes for each study before combining them and examined moderators one-by-one by splitting the data into small subgroups. The second meta-analysis (Burnette et al., 2023) modeled the variation of effects within studies-across subgroups and outcomes-and applied modern, multilevel metaregression methods. The former concluded that growth mindset effects are biased, but the latter yielded nuanced conclusions consistent with theoretical predictions. We explain why the practices followed by the latter meta-analysis were more in line with best practices for analyzing large and heterogeneous literatures. Further, an exploratory re-analysis of the data showed that applying the modern, heterogeneity-attuned methods from Burnette et al. (2023) to the data set employed by Macnamara and Burgoyne (2023) confirmed Burnette et al.'s conclusions; namely, that there was a meaningful, significant effect of growth mindset in focal (at-risk) groups. This article concludes that heterogeneity-attuned meta-analysis is important both for advancing theory and for avoiding the boom-or-bust cycle that plagues too much of psychological science.

This study examines how collaborative activity among students and the teacher to investigate disciplinary questions, which we term 'joint exploration', is established and maintained in a secondary mathematics classroom. Although collaborative and active learning is increasingly sought after in mathematics classrooms, studies of instances of joint exploration remain relatively rare. In this study, we use the theoretical perspective of positioning to conceptualize joint exploration as involving the negotiation among participants to position students with epistemic authority and agency. Using a constant comparative method, we use classroom video data of two episodes containing joint exploration and closely analyse the shifts in epistemic positioning within them. We find that shifts in epistemic positioning, especially with respect to students positioning one another with epistemic authority and exercising epistemic agency, help to support continued joint exploration. We also find that the teacher can play an important role in decentring themselves as the epistemic authority. In addition to these findings, this study contributes a distinction in epistemic authority and agency, as we explain how the two concepts are related and involved in establishing and maintaining joint exploration. Dans cette etude, on cherche a comprendre comment l'activite collaborative entre les eleves et l'enseignant pour analyser des questions liees a la discipline, ce que nous appelons << exploration conjointe >>, est etablie et maintenue dans une classe de mathematiques du secondaire. Bien que l'apprentissage collaboratif et actif soit de plus en plus recherche dans les classes de mathematiques, les etudes portant sur les exemples d'exploration conjointe restent relativement rares. Dans cette etude, nous utilisons l'approche theorique du positionnement pour conceptualiser l'exploration conjointe sur la base d'une negociation entre les participants afin de doter les eleves d'une autorite epistemique et d'une capacite d'agir. A l'aide d'une methode comparative soutenue, nous employons des donnees video montrant deux episodes d'exploration conjointe en classe et analysons de pres les changements de positionnement epistemique observes dans ces episodes. Nous constatons que les variations de positionnement epistemique, en particulier en ce qui concerne les eleves qui s'attribuent les uns les autres une autorite epistemique et qui exercent egalement une capacite d'agir epistemique, contribuent a soutenir le maintien de l'exploration conjointe. Nous remarquons egalement que l'enseignant peut jouer un role important en s'eloignant de son role d'autorite epistemique. Au-dela de ces resultats, cette etude etablit une distinction entre l'autorite epistemique et la capacite d'agir, alors que nous expliquons comment les deux concepts sont lies et impliques dans la mise en oe uvre et le maintien de l'exploration conjointe.

Peers' negative police encounters may have collateral consequences and shape adolescents' relationship with authority figures, including those in the school context. Due to the expansion of law enforcement in schools (e.g., school resource officers) and nearby neighborhoods, schools include spaces where adolescents witness or learn about their peers' intrusive encounters (e.g., stop-and-frisks) with the police. When peers experience intrusive police encounters, adolescents may feel like their freedoms are infringed upon by law enforcement and subsequently view institutions, including schools, with distrust and cynicism. In turn, adolescents will likely engage in more defiant behaviors to reassert their freedoms and express their cynicism toward institutions. To test these hypotheses, the present study leveraged a large sample of adolescents (N = 2,061) enrolled in classrooms (N = 157) and examined whether classmates' police intrusion predicted adolescents' engagement in school-based defiant behaviors over time. Results suggest that classmates' intrusive police experiences in the fall term predicted higher levels of adolescents' engagement in defiant behaviors at the end of the school year, regardless of adolescents' own history of direct police intrusive encounters. Adolescents' institutional trust partially mediated the longitudinal association between classmates' intrusive police encounters and adolescents' defiant behaviors. Whereas past studies have largely focused on individual experiences of police encounters, the present study uses a developmental lens to understand how the effects of law enforcement-perpetuated intrusion on adolescent development may operate through peer interactions. Implications for legal system policies and practices are discussed.

Data visualizations are routinely used for STEM faculty development to support equitable teaching practices. Yet, little is known about how instructors interpret such data visualizations. This interview study fills a key gap by providing insight into how STEM educators make sense of visualizations. We report on cognitive interviews with 17 participants who were shown eight different data visualizations depicting racial inequities in classroom participation. The participants were asked to interpret whether the scenarios were equitable and answer questions about the distribution of participation. We report on which visualizations participants were able to interpret most accurately, and how particular visualizations supported thinking about inequity. No single visualization was most effective in all cases, and critically, we found that not all visualizations were equally effective for identifying inequities, and that different types of visualizations drew attention to different aspects of inequity (e.g., individual disparities vs. group-level disparities). We also provide data on how participants differentiated between equity and equality. Thus, the present study provides useful information for professional developers about which types of visualizations may be most effective for different purposes and highlights the need for multiple representations of racial inequity. © The Author(s), under exclusive licence to Springer Nature Switzerland AG 2023.

Meta-analytic structural equation modeling was used to estimate the relative contributions of general cognitive ability or g (defined by executive functions, short-term memory, and intelligence) and basic domain-specific mathematical abilities to performance in more complex mathematics domains. The domain-specific abilities included mathematics fluency (e.g., speed of retrieving basic facts), computational skills (i.e., accuracy at solving multi-step arithmetic, algebra, or geometry problems), and word problems (i.e., mathematics problems presented in narrative form). The core analysis included 448 independent samples and 431,344 participants and revealed that g predicted performance in all three mathematics domains. Mathematics fluency contributed to the prediction of computational skills, and both mathematics fluency and computational skills predicted word problem performance, controlling g. The relative contribution of g was consistently larger than basic domain-specific abilities, although the latter may be underestimated. The patterns were similar across younger and older individuals, individuals with and without a disability (e.g., learning disability), concurrent and longitudinal assessments, and family socioeconomic status, and have implications for fostering mathematical development.

Creativity research often relies on human raters to judge the novelty of participants’ responses on open-ended tasks, such as the Alternate Uses Task (AUT). Albeit useful, manual ratings are subjective and labor intensive. To address these limitations, researchers increasingly use automatic scoring methods based on a natural language processing technique for quantifying the semantic distance between words. However, many methodological choices remain open on how to obtain semantic distance scores for ideas, which can significantly impact reliability and validity. In this project, we propose a new semantic distance-based method, maximum associative distance (MAD), for assessing response novelty in AUT. Within a response, MAD uses the semantic distance of the word that is maximally remote from the prompt word to reflect response novelty. We compare the results from MAD with other competing semantic distance-based methods, including element-wise-multiplication—a commonly used compositional model—across three published datasets including a total of 447 participants. We found MAD to be more strongly correlated with human creativity ratings than the competing methods. In addition, MAD scores reliably predict external measures such as openness to experience. We further explored how idea elaboration affects the performance of various scoring methods and found that MAD is closely aligned with human raters in processing multi-word responses. The MAD method thus improves the psychometrics of semantic distance for automatic creativity assessment, and it provides clues about what human raters find creative about ideas.

Creative thinking is important for success in the fields of science, technology, engineering, and mathematics (STEM). Yet creativity in STEM is perhaps the most under-researched question in the creativity literature, with little known about the neurocognitive mechanisms supporting scientific creative thinking abilities, such as hypothesis generation. In the present functional magnetic resonance imaging study, undergraduate STEM majors (n = 47) completed a scientific hypothesis generation task (thinking of novel/plausible explanations for hypothetical scenarios) and a control task (thinking of synonyms to replace a word in a hypothetical scenario). Multivariate pattern analysis identified a whole-brain network supporting hypothesis generation, including hubs of the default (posterior cingulate cortex [PCC]), salience (right anterior insula [AI]), and semantic control (left inferior frontal gyrus [IFG]) networks. Using these network hubs as seed regions, we found increased between-network functional connectivity during hypothesis generation, including stronger coupling between semantic control (IFG) and posterior default regions (PCC and bilateral angular gyrus) and stronger coupling between salience (AI) and default regions, alongside weaker within-network functional connectivity. Our results indicate that scientific creative thinking involves increased cooperation among the default, salience, and control networks-similar to creative thinking in other domains-potentially reflecting a coordination of spontaneous/generative and controlled/evaluative processes to construct original explanations for scientific phenomena.

Creativity research commonly involves recruiting human raters to judge the originality of responses to divergent thinking tasks, such as the alternate uses task (AUT). These manual scoring practices have benefited the field, but they also have limitations, including labor-intensiveness and subjectivity, which can adversely impact the reliability and validity of assessments. To address these challenges, researchers are increasingly employing automatic scoring approaches, such as distributional models of semantic distance. However, semantic distance has primarily been studied in English-speaking samples, with very little research in the many other languages of the world. In a multilab study (N= 6,522 participants), we aimed to validate semantic distance on the AUT in 12 languages: Arabic, Chinese, Dutch, English, Farsi, French, German, Hebrew, Italian, Polish, Russian, and Spanish. We gathered AUT responses and human creativity ratings (N= 107,672 responses), as well as criterion measures for validation (e.g., creative achievement).We compared two deep learning-based semantic models—multilingual bidirectional encoder representations from transformers and cross-lingual language model RoBERTa—to compute semantic distance and validate this automated metric with human ratings and criterion measures. We found that the top-performing model for each language correlated positively with human creativity ratings, with correlations ranging from medium to large across languages. Regarding criterion validity, semantic distance showed small-to-moderate effect sizes (comparable to human ratings) for openness, creative behavior/achievement, and creative self-concept. We provide open access to our multilingual dataset for future algorithmic development, along with Python code to compute semantic distance in 12 languages. © 2023 American Psychological Association

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.