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Abstract Creativity is a key 21st-century skill and a consistent predictor of academic learning outcomes. Despite decades of research on creativity and learning, little is known about the cognitive mechanisms underlying their relationship. In two studies, we examined whether creativity supports associative learning through associative thinking—the ability to generate novel word associations—an ability central to creativity which has not been previously tied to associative learning. In Study 1, we found that students who generated more novel word associations learned more words on a foreign language learning test 24 h later. In Study 2, we replicated and extended the effect to naturalistic creativity tasks (i.e., writing short stories and sketching line drawings), finding associative thinking mediated the relationship between creativity and associative learning. Importantly, both studies controlled for general intelligence. Our findings suggest that creativity’s contribution to learning operates partly through a shared cognitive capacity for making new connections. 

Abstract Creativity is increasingly recognized as a core competency for the 21st century, making its development a priority in education, research, and industry. To effectively cultivate creativity, researchers and educators need reliable and accessible assessment tools. Recent software developments have significantly enhanced the administration and scoring of creativity measures; however, existing software often requires expertise in experiment design and computer programming, limiting its accessibility to many educators and researchers. In the current work, we introduce CAP—the Creativity Assessment Platform—a free web application for building creativity assessments, collecting data, and automatically scoring responses (cap.ist.psu.edu). CAP allows users to create custom creativity assessments in ten languages using a simple, point-and-click interface, selecting from tasks such as the Short Story Task, Drawing Task, and Scientific Creative Thinking Test. Users can automatically score task responses using machine learning models trained to match human creativity ratings—with multilingual capabilities, including the new Cross-Lingual Alternate Uses Scoring (CLAUS), a large language model achieving strong prediction of human creativity ratings in ten languages. CAP also provides a centralized dashboard to monitor data collection, score assessments, and automatically generate text for a Methods section based on the study’s tasks, metrics, and instructions—with a single click—promoting transparency and reproducibility in creativity assessment. Designed for ease of use, CAP aims to democratize creativity measurement for researchers, educators, and everyone in between. 

Abstract Transdisciplinary research is increasingly important for solving complex societal problems. Institutions aim to train graduate students to engage in transdisciplinary research. However, limited evidence exists regarding the process by which students learn transdisciplinary thinking. This qualitative study explored graduate students’ pathways of growth toward transdisciplinary thinking during one semester. The students were enrolled in a professional development course as part of a training grant. We examined artifacts from the course through multiple rounds of thematic coding. We used a grounded theory approach to gain insights into how graduate students navigate their journey toward transdisciplinary thinking. We propose a model of this journey. It traces students’ trajectories from prior experiences, through reflexive thinking about several crucial skills and dispositions, towards a transdisciplinary “prism” that transforms their thinking. We conclude that becoming a transdisciplinary researcher is not a matter of acquiring competencies, but a life-long process. Fostering this process may require fundamental reimagining of graduate education. 

Abstract Over the past decades, bilingualism researchers have come to a consensus around a fairly strong view of nonselectivity in bilingual speakers, often citing Van Hell and Dijkstra (2002) as a critical piece of support for this position. Given the study’s continuing relevance to bilingualism and its strong test of the influence of a bilingual’s second language on their first language, we conducted an approximate replication of the lexical decision experiments in the original study (Experiments 2 and 3) using the same tasks and—to the extent possible—the same stimuli. Unlike the original study, our replication was conducted online with Dutch–English bilinguals (rather than in a lab with Dutch–English–French trilinguals). Despite these differences, results overall closely replicated the pattern of cognate facilitation effects observed in the original study. We discuss the replication of outcomes and possible interpretations of subtle differences in outcomes and make recommendations for future extensions of this line of research. 

We examined the neural correlates underlying the semantic processing of native- and nonnative-accented sentences, presented in quiet or embedded in multi-talker noise. Implementing a semantic violation paradigm, 36 English monolingual young adults listened to American-accented (native) and Chinese-accented (nonnative) English sentences with or without semantic anomalies, presented in quiet or embedded in multi-talker noise, while EEG was recorded. After hearing each sentence, participants verbally repeated the sentence, which was coded and scored as an offline comprehension accuracy measure. In line with earlier behavioral studies, the negative impact of background noise on sentence repetition accuracy was higher for nonnative-accented than for native-accented sentences. At the neural level, the N400 effect for semantic anomaly was larger for nativeaccented than for nonnative-accented sentences, and was also larger for sentences presented in quiet than in noise, indicating impaired lexical-semantic access when listening to nonnative-accented speech or sentences embedded in noise. No semantic N400 effect was observed for nonnative-accented sentences presented in noise. Furthermore, the frequency of neural oscillations in the alpha frequency band (an index of online cognitive listening effort) was higher when listening to sentences in noise versus in quiet, but no difference was observed across the accent conditions. Semantic anomalies presented in background noise also elicited higher theta activity, whereas processing nonnative-accented anomalies was associated with decreased theta activity. Taken together, we found that listening to nonnative accents or background noise is associated with processing challenges during online semantic access, leading to decreased comprehension accuracy. However, the underlying cognitive mechanism (e.g., associated listening efforts) might manifest differently across accented speech processing and speech in noise processing.