The cognitive-motivational concepts of curiosity and creativity are often viewed as intertwined. Yet, despite the intuitively strong linkage between these two concepts, the existing cognitive-behavioral evidence for a curiosity-creativity connection is not strong, and is nearly entirely based on self-report measures. Using a new lab-based Curiosity Q&A task we evaluate to what extent behaviorally manifested curiosity—as revealed in autonomous inquiry and exploration—is associated with creative performance. In a preregistered study (N = 179) we show that, as hypothesized, the novelty of the questions that participants generated during the Curiosity Q&A Task significantly positively correlated with the originality of their responses on a divergent-thinking task (the conceptually-based Alternative Uses Task). Additionally, the extent to which participants sought out information that was implicitly missing in the presented factual stimuli ("gap-related information foraging") positively correlated with performance on two predominantly convergent-thinking tasks (the Remote Associates Task and Analogy Completion). Question asking, topic-related information foraging, and creative performance correlated with trait-based "interest-type" curiosity oriented toward exploration and novelty, but not with "deprivation-type" curiosity focused on dispelling uncertainty or ignorance. Theoretically and practically, these results underscore the importance of continuing to develop interventions that foster both creative thinking and active autonomous inquiry.

While universalism is a foundational principle of science, a growing stream of research finds that scientific contributions are evaluated differently depending on the gender of the author, with women tending to receive fewer citations relative to men, even for work of comparable quality. Strikingly, research also suggests that these gender gaps are visible even under blinded review, wherein the evaluator is not aware of the gender of the author. In this article, we consider whether gender differences in writing styles-how men and women communicate their work-may contribute to these observed gender gaps. We ground our investigation in a previously established framework for characterizing the linguistic style of written text, which distinguishes between two sets of features-informational (i.e., features that emphasize facts) and involved (i.e., features that emphasize relationships). Using a large, matched sample of academic papers and patents, we find significant differences in writing style by gender; women use more involved features in their writing, a pattern that holds universally across fields. The magnitude of the effect varies across fields, with larger gender differences observed in the social sciences and arts humanities and smaller gaps in the physical sciences and technology. Subsequently, we show that gender differences in writing style may have parallels in reading preferences; papers and patents with more informational features tend to be cited more by men, while those with more involved features tend to be cited more by women, even after controlling for the gender of the author, inventor, and patent attorney. Our findings suggest that formal written text is not devoid of personal character, which could contribute to bias in evaluation, thereby compromising the norm of universalism.

Curiosity motivates the search for missing information, driving learning, scientific discovery, and innovation. Yet identifying that there is a gap in one's knowledge is itself a critical step, and may demand that one formulate a question to precisely express what is missing. Our work captures the integral role of self-generated questions during the acquisition of new information, which we refer to as active-curiosity-driven learning. We tested active-curiosity-driven learning using our "Curiosity Question & Answer Task" paradigm, where participants (N=135) were asked to generate questions in response to novel, incomplete factual statements and provided the opportunity to forage for answers. We also introduce new measures of question quality that express how well questions capture stimulus and foraging information. We hypothesized that active question asking should influence behavior across the stages of our task by increasing the probability that participants express curiosity, forage for answers, and remember what they had thereby discovered. We found that individuals who asked a high number of quality questions experienced elevated curiosity, were more likely to pursue missing information that was semantically related to their questions, and more likely to retain the information on a later cued recall test. Additional analyses revealed that curiosity played a predominant role in motivating participants to forage for missing information, and that both curiosity and satisfaction with the acquired information boosted memory recall. Overall our results suggest that asking questions enhances the value of missing information, with important implications for learning and discovery of all forms.

Curiosity motivates the search for missing information, driving learning, scientific discovery, and innovation. Yet identifying that there is a gap in one’s knowledge is itself a critical step, and may demand that one formulate a question to precisely express what is missing. We provide a model of active-curiosity-driven learning that captures the integral role of self-generated questions during the acquisition of new information. We tested our model using our “Curiosity Question & Answer Task” paradigm, where participants (N=136) were asked to generate questions in response to novel, incomplete factual statements and provided the opportunity to forage for answers. We also introduce new measures of question quality that express how well questions capture stimulus and foraging information. We hypothesized that active question asking should influence behavior across the stages of our task by increasing the probability that participants express curiosity, forage for answers, and remember what they had thereby discovered. We found that individuals who asked a high number of quality questions demonstrated boosted curiosity, were more likely to pursue missing information, and more likely to retain the information on a later cued recall test. Additional analyses revealed that curiosity played a predominant role in motivating participants to forage for missing information, but satisfaction with the acquired information was a better indicator of memory recall than curiosity. Overall our results suggest that asking questions enhances the value of missing information, with important implications for learning and discovery of all forms.

How does scientific knowledge grow? For generations, this question has occupied a central place in the philosophy of science, stimulating heated debates, and yielding no clear consensus. Many proposed explanations can be understood in terms of whether and how they view the expansion of knowledge as proceeding through the organization of scientific concepts into core/periphery structures, wherein the core encompasses foundational knowledge and the periphery consists of emergent ideas. Here, we examine these views empirically, performing a large-scale analysis of the physical and social sciences, spanning five decades. Using techniques from natural language processing, we create semantic networks of concepts, wherein single-and multi-word noun phrases become linked when they are used in the same paper abstract. For both the physical and social sciences, we observe increasingly rigid cores accompanied by the proliferation of periphery concepts. In the physical sciences, these changes coincide with an increasing number of cores, while in the social sciences, the number of cores is decreasing. In subsequent analyses, we examine the relationship between core/periphery organization and the growth of scientific knowledge, finding that scientific works are less innovative in fields with smaller cores, cores with less conceptual churn, and an overall larger number of cores, the latter of which is also associated with less scientific consensus. Overall, our findings suggest that while the organization of scientific concepts is important for the growth of knowledge, the mechanisms vary across fields and time.