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Interactions with classroom friends may be an important contributor to first and second language development, but to date this hypothesis has not been tested. Using a longitudinal design, the current study investigated the relationship between classroom friendships and oral language development in children. In 8 classrooms, we assessed the relationship between oral language skills and classroom social networks. Across the classrooms, 165 primary school children in Austria (83 boys; 119 L2 learners; age: 6-10) were assessed on oral language proficiency at the beginning of the school year (T1) and 6-7 months later (T2). Results indicated that the more reciprocal best friendships at T1, the greater language improvement at T2. Language improvement was strongest among friends with moderate differences in language proficiency, regardless of whether students were first or second language learners. These results underline the importance of positive social relations at school for language learning broadly.

With the recent proliferation of advanced artificial intelligence (AI) models capable of mimicking human artworks, AI creations might soon replace products of human creativity, although skeptics argue that this outcome is unlikely. One possible reason this may be unlikely is that, independent of the physical properties of art, we place great value on the imbuement of the human experience in art. An interesting question, then, is whether and why people might prefer human-compared to AI-created artworks. To explore these questions, we manipulated the purported creator of pieces of art by randomly assigning a "Human-created" or "AI-created" label to paintings actually created by AI, and then assessed participants' judgements of the artworks across four rating criteria (Liking, Beauty, Profundity, and Worth). Study 1 found increased positive judgements for human- compared to AI-labelled art across all criteria. Study 2 aimed to replicate and extend Study 1 with additional ratings (Emotion, Story, Meaningful, Effort, and Time to create) intended to elucidate "why" people more-positively appraise Human-labelled artworks. The main findings from Study 1 were replicated, with narrativity (Story) and perceived effort behind artworks (Effort) moderating the label effects ("Human-created" vs. "AI-created"), but only for the sensory-level judgements (Liking, Beauty). Positive personal attitudes toward AI moderated label effects for more-communicative judgements (Profundity, Worth). These studies demonstrate that people tend to be negatively biased against AI-created artworks relative to purportedly human-created artwork, and suggest that knowledge of human engagement in the artistic process contributes positively to appraisals of art.

Studies of everyday creativity suggest that some people are like creative omnivores, dabbling in a broad range of creative pursuits, but others are like picky eaters, focusing on a single creative passion. A week-long experience sampling study examined the breadth vs depth of 125 university students' everyday creative activities. Several times a day, people were asked if they were doing something creative, and if they were, to describe what they were doing. Diversity statistics quantified the variety (number of distinct domains) and balance (the relative predominance of any domain) of their creative activities. The sample varied widely in both aspects of diversity, reflecting differences in whether people's creative efforts were relatively broad or focused. Notably, people who were high in openness to experience showed significantly higher variety (they did more kinds of creative activities) yet lower balance (one or two activities predominated), suggesting that they had a broad creative diet but a few favorite foods.

Existing research has consistently supported a relationship between creative achievement and specific personality traits (e.g. openness to experience). However, such work has largely focused on univariate associations, potentially obscuring complex interactions among multiple personality factors, rendering an incomplete picture of the creative personality. We applied a psychometric network approach to characterize the multidimensional personality structure of highly creative individuals in the arts ("artists") and sciences ("scientists"), using data from three samples (N = 4,015): college students, a representative adult sample, and the Big-C project of eminent creative professionals. Replicating past work, we found that artists showed reliably higher levels of openness to experience compared to scientists and a control group of less creative people. Psychometric network analysis revealed that artists were characterized by higher connectivity (i.e. co-occurrence) with other personality traits for openness, indicating that openness may be more heterogeneous in how it co-occurs with other personality traits in highly creative people. Across all three samples, we found that the scientists' personality network structure was more cohesive than the personality network of artists and the control group, indicating greater homogeneity in the personality characteristics of scientists. Our findings uncover a constellation of traits that give rise to creative achievement in the arts and sciences.

A large body of research has revealed that viewing example image stimuli tends to constrain creative idea generation. However, the neurocognitive mechanisms underlying such visual fixation in creative cognition are unclear. In the present experiment, we explored whether example images impacted creative imagination and patterns of neural activity within brain regions associated with visual object recognition. Participants first viewed example images (ambiguous line drawings) accompanied by high-constraint and low-constraint labels. High-constraint labels resembled the line drawings, whereas low constraint labels did not. Next, participants imagined new labels for the same line drawings, with the initial labels removed. Consistent with our predictions, semantic distance analysis comparing cue labels to newly generated labels showed lower average semantic distance (i.e., less creative ideas) on high-constraint trials compared to low-constraint trials. Using representational similarity analysis, we also demonstrated that neural pattern similarity was anticorrelated (less similar) from object recognition to high-constraint imagination trials within the right inferior temporal gyrus, right middle temporal gyrus, and right superior occipital gyrus. Broadly, these findings suggest that salient visual examples may guide the formation of strong mental representations that constrain creative imagination. This research also offers a first step toward identifying neurocognitive signatures associated with the effortful process of producing new, creative ideas following exposure to fixating examples -- particularly at the early level of object recognition/representation in the ventral visual stream.

Increasing research efforts are focused on explaining the cognitive bases of creativity. However, it remains unclear when and how cognitive factors such as intelligence and executive function uniquely contribute to performance on creative thinking tasks. Although a relationship between fluid intelligence (Gf) and creative cognition has been well-documented, the underlying mechanism of this relation is unknown. Here, we test one possible mechanism of the Gf--creativity association -- attention control (AC) -- given AC's strong association with Gf and its theoretical relevance to creative cognition. We also examine the role of mind wandering (i.e., task-unrelated thought), a failure of AC that is potentially beneficial to creativity. Using latent variable and bifactor models, we investigated the unique contributions of AC to divergent thinking -- above the influence of "Gf" -- evaluating the specific and general contributions of AC, "Gf," and mind wandering to divergent thinking. We found that a general executive factor (i.e., of the common variance to AC, mind wandering, and Gf indicators) significantly predicted divergent thinking originality ([beta] =0.40, p <0.001) above and beyond specific Gf and mind wandering factors. Importantly, in the bifactor model, mind wandering was a nonsignificant, negative predictor of divergent thinking performance, and the residual effects of "Gf" were no longer significant, indicating that the relationship between "Gf" and divergent thinking is explained by shared variance with a common executive attention factor. This study provides novel evidence suggesting that the relationship between Gf and divergent thinking may be largely driven by the top-down control of attention.

Establishing measurement invariance (MI) is crucial for the validity and comparability of psychological measurements across different groups. If MI is violated, mean differences among groups could be due to the measurement rather than differences in the latent variable. Recent research has highlighted the prevalence of inaccurate MI models in studies, often influenced by the software used. Additionally, unequal group sample sizes, noninvariant referent indicators, and reliance on data-driven methods reduce the power of traditional SEM methods. Network psychometrics lacks methods comparing network structures conceptually similar to MI. We propose a more conceptually consistent method within the Exploratory Graph Analysis (EGA) framework using network loadings, analogous to factor loadings. Our simulation study demonstrates that this method offers comparable or improved power, especially in scenarios with smaller or unequal sample sizes and lower noninvariance effect sizes, compared to SEM MI testing. [ABSTRACT FROM AUTHOR]

How do people come up with humorous ideas? In creative cognition research, exposure to good examples sometimes causes fixation (people get "stuck" on the examples) but other times sparks inspiration (people's responses are more creative). The present research examined the effects of funny and unfunny examples on joke production. A sample of 175 adults read scenarios that they completed with funny responses. All participants were instructed to be funny, but before responding they read (a) funny responses as examples of good responses to emulate, (b) unfunny responses as examples of poor responses to avoid, or (c) no examples. The participants' own responses were rated for funniness and for similarity to the example responses, and response times were recorded. Reading either funny or unfunny examples, compared to no examples, caused people to come up with funnier jokes. Similarity to the examples was low in all conditions, so fixation was relatively modest, but people who saw unfunny examples spent more time coming up with their responses. Taken together, the findings support the growing literature showing that examples are often inspiring rather than constraining, and they imply that good and bad examples spark creative thought via different paths.