Studying 5.6 million biomedical science articles published over three decades, we reconcile conflicts in a long-standing interdisciplinary literature on scientists' life-cycle productivity by controlling for selective attrition and distinguishing between research quantity and quality. While research quality declines monotonically over the career, this decline is easily overlooked because higher ability authors have longer publishing careers. Our results have implications for broader questions of human capital accumulation over the career and federal research policies that shift funding to early-career researchers-while funding researchers at their most creative, these policies must be undertaken carefully because young researchers are less able on average.

IntroductionThis study reports on a classroom intervention where upper-elementary students and their teacher explored the biological phenomena of eutrophication using the Modeling and Evidence Mapping (MEME) software environment and associated learning activities. The MEME software and activities were designed to help students create and refine visual models of an ecosystem based on evidence about the eutrophication phenomena. The current study examines how students utilizing this tool were supported in developing their mechanistic reasoning when modeling complex systems. We ask the following research question: How do designed activities within a model-based software tool support the integrations of complex systems thinking and the practice of scientific modeling for elementary students? MethodsThis was a design-based research (DBR) observational study of one classroom. A new mechanistic reasoning coding scheme is used to show how students represented their ideas about mechanisms within their collaboratively developed models. Interaction analysis was then used to examine how students developed their models of mechanism in interaction. ResultsOur results revealed that students' mechanistic reasoning clearly developed across the modeling unit they participated in. Qualitative coding of students' models across time showed that students' mechanisms developed from initially simplistic descriptions of cause and effect aspects of a system to intricate connections of how multiple entities within a system chain together in specific processes to effect the entire system. Our interaction analysis revealed that when creating mechanisms within scientific models students' mechanistic reasoning was mediated by their interpretation/grasp of evidence, their collaborative negotiations on how to link evidence to justify their models, and students' playful and creative modeling practices that emerged in interaction. DiscussionIn this study, we closely examined students' mechanistic reasoning that emerge in their scientific modeling practices, we offer insights into how these two theoretical frameworks can be effectively integrated in the design of learning activities and software tools to better support young students' scientific inquiry. Our analysis demonstrates a range of ways that students represent their ideas about mechanism when creating a scientific model, as well as how these unfold in interaction. The rich interactional context in this study revealed students' mechanistic reasoning around modeling and complex systems that may have otherwise gone unnoticed, suggesting a need to further attend to interaction as a unit of analysis when researching the integration of multiple conceptual frameworks in science education.

In spring 2020, the COVID-19 pandemic thrust nearly 56 million students in the United States into remote education. By fall 2020, states' and school districts' differing public health measures resulted in the adoption of varying COVID-adapted learning modalities (i.e., in-person, remote, and hybrid). Using daily diary data with a nationally representative sample (N = 517, M-age = 14.65 years), we investigated whether adolescents' academic engagement and connectedness to their teachers and classmates differed by COVID-adapted learning modalities. We also assessed whether adolescent connectedness mediated the link between learning modality and academic engagement. Results revealed that academic engagement and connectedness to teachers and classmates were higher for in-person learners than for students in hybrid and remote learning modalities. Moreover, students' connectedness to classmates and teachers explained the relationship between learning modality and academic engagement.

In spring 2020, U.S. schools universally transitioned to online learning due to the COVID-19 pandemic's onset, thus creating a natural experiment for examining adolescents' risk and resilience during an ongoing school crisis response. This longitudinal study used a daily-diary approach to investigate the role of social support in the link between remote learning and psychological well-being across 64 days among a national sample of adolescents (n = 744; 42% Black, 36% White, 22% Other ethnicity/race; 41% boys; 72% eligible for free/reduced-priced lunch; Mage=14.60, SDage=1.71, age-range = 12-17 years). On days when youth attended remote learning, they reported lower daily positive affect, more daily stress, and higher parent social support. There were no significant differences in the effect of remote learning on affect or stress by race or economic status. On days when youth experienced more parent support, they reported lower daily stress and negative affect and higher daily positive affect. On days when youth experienced more peer support, they reported higher daily positive affect. Overall, the study highlights the impact of pandemic-onset remote learning on adolescents' psychological well-being and emphasizes the need for future research on school crisis contingency planning to address these challenges.

Word learning encompasses the understanding of interconnected clusters of words, where the comprehension of one word aids in the learning of another. Semantic networks, which have a long history in cognitive science, are commonly employed to explore these semantic relationships. However, limited research has been conducted on adults’ use of semantically relevant conversations in the field of early childhood education, and there is insufficient information regarding contextual factors influencing the development of semantic networks. The present study investigated the extent to which the use and effectiveness of semantically relevant conversations vary across activity contexts. This study analyzed data from the Home-School Study of Language and Literacy Development (HSLLD) Corpus available in the CHILDES database, focusing on a subset of 62 children. This study utilized four statistical features to describe the structure of semantic networks: short path length, diameter, density, and clustering coefficient. The following findings emerged: (1) Book reading displayed a significantly greater diameter than toy play and mealtime, indicating that there exist specific pairs of concepts or words within its semantic networks that are notably more distant from each other than in the other two activity settings. (2) Toy play exhibited a significantly greater density in comparison to book reading and mealtime, suggesting a higher degree of overlap or interdependence among the concepts within its semantic networks. (3) Book reading demonstrated a significantly greater clustering coefficient compared to toy play and mealtime, signifying the existence of cohesive word communities or groups of words characterized by dense internal connections. (4) Adults’ use of semantically relevant conversations during book reading was positively associated with children’s lexical diversity. © 2023 by the authors.

Semantic distance scoring provides an attractive alternative to other scoring approaches for responses in creative thinking tasks. In addition, evidence in support of semantic distance scoring has increased over the last few years. In one recent approach, it has been proposed to combine multiple semantic spaces to better balance the idiosyncratic influences of each space. Thereby, final semantic distance scores for each response are represented by a composite or factor score. However, semantic spaces are not necessarily equally weighted in mean scores, and the usage of factor scores requires high levels of factor determinacy (i.e., the correlation between estimates and true factor scores). Hence, in this work, we examined the weighting underlying mean scores, mean scores of standardized variables, factor loadings, weights that maximize reliability, and equally effective weights on common verbal creative thinking tasks. Both empirical and simulated factor determinacy, as well as Gilmer-Feldt's composite reliability, were mostly good to excellent (i.e., > .80) across two task types (Alternate Uses and Creative Word Association), eight samples of data, and all weighting approaches. Person-level validity findings were further highly comparable across weighting approaches. Observed nuances and challenges of different weightings and the question of using composites vs. factor scores are thoroughly provided.

Though adults tend to endorse the stereotype that boys are better than girls in math, children tend to favor their own gender or be gender egalitarian. When do individuals start endorsing the traditional stereotype that boys are better? Using two longitudinal U.S. datasets that span 1993 to 2011, we examined three questions: (1) What are the developmental changes in adolescents' gender stereotypes about math abilities from early to late adolescence? (2) Do the developmental changes vary based on gender and race/ethnicity? (3) Are adolescents' stereotypes related to their math motivational beliefs? Finally, (4) do these patterns replicate across two datasets that vary in historical time? Adolescents in grades 8/9 and 11 were asked whether girls or boys are better at math (n's = 1186 and 23,340, 49-53% girls, 30-54% White, 13-60% Black, 1-22% Latinx, and 2% to 4% Asian). Early adolescents were more likely to be gender egalitarian or favor their own gender. By late adolescence, adolescents' stereotypes typically shifted towards the traditional stereotype that boys are better. In terms of race/ethnicity, White and Asian adolescents significantly favored boys, whereas Black and Latinx adolescents were more likely to endorse gender egalitarian beliefs. Adolescents' stereotypes were significantly related to their expectancy beliefs, negatively for girls and positively for boys.

The associative theory posits that creativity relates to people's ability to connect remote associations to form new ideas, based on the structure of their semantic memory. This theory has spurred several recent studies connecting semantic memory structure and associative thinking to creativity, capitalizing on advances in computational methods. To date, however, this research has almost exclusively focused on assessing creativity in the general population (e.g., assessed via divergent thinking tests), with far less work examining the role of associative thinking in eminently-creative individuals across the arts and sciences. Leveraging data collected as part of the Big-C Project-a sample of world-renowned visual artists (VIS) and scientists, and an intelligence-matched comparison group-we tested whether the ability to generate remote word associations differs as a function of creative expertise. Specifically, we used distributional semantic models to calculate the semantic distance of word associations across three conditions: a free association condition and two goal-directed conditions (common association and uncommon association). We found an interaction between domain expertise and association condition: while artists generated more distant associations overall, this effect was driven by substantially more distant responses in the free association condition. Our findings indicate that VIS spontaneously produce more remote associations-potentially due to a more interconnected semantic memory network structure-but that creative expertise is less relevant for producing associations that require goal-directed cognitive search. The findings are interpreted in the context of the ongoing debate on the domain-generality and domain-specificity of creativity.

Learning coding during early childhood is an effective way for children to practice computational thinking. As-pects of children's motivation can increase the likelihood that children approach computational thinking activities with enthusiasm and deep engagement. Gender inequities may interfere with children's readiness to take advan-tage of opportunities to build computational thinking skills through activities such as coding. Societal stereotypes can reduce young girls' motivation to engage with computer science, preventing them from gaining benefits from coding activities designed to support computational thinking. This study examined children's gender stereotypes as well as children's own motivation for computer coding in 363 first-through third-grade children. We assessed gender differences in both stereotypes and motivation, as well as links between the stereotypes that individual children held and their own motivation. Children generally endorsed stereotypes about interest and ability for computer coding that favored their own-gender group, although third-grade girls reported gender-egalitarian beliefs about interest in coding. There were no gender differences in children's motivation for computer cod-ing in terms of their own interest, sense of belonging, or ability self-concepts. Children's stereotypes about their own-gender group were significantly positively correlated with their own motivation for computer coding. These findings suggest that early childhood represents an excellent age for children to begin building computational thinking skills, before girls endorse negative stereotypes about their gender's interest in computer science.

What factors influence predictions of creative performance? Prior work indicates that images can skew predictions in the contexts of learning, memory, and decision making, but little work has devoted attention to the metacognitive effects of images in creative thinking. Metacognitive frameworks indicate that people often base predictions of performance on the subjective ease with which related information comes to mind. The present experiments tested whether the presence of object photographs in the alternate uses task (AUT) inflates predictions of creativity. In Experiments 1-4, participants made ratings about their predictions of creative performance for various objects in the AUT either with or without photographs of the object. Participants provided higher ratings and were faster to make ratings in the image than no-image condition. In Experiment 5, participants actually attempted to generate creative uses for the objects, half of which were accompanied by object photographs. Creativity scores for these responses were lower in the image condition than no-image condition, but participants' retrospective judgments indicated the opposite. These results provide a novel extension of metacognitive work showing that images inflate predictions of performance and fit with prior research showing that images can limit creativity.