ABSTRACT The PISA assessment 2022 of creative thinking was a moonshot effort that introduced significant advancements over existing creativity tests, including a broad range of domains (written, visual, social, and scientific), implementation in many languages, and sophisticated scoring methods. PISA 2022 demonstrated the general feasibility of assessing creative thinking ability comprehensively at an international scale. However, the complexity of its assessment approach—such as time‐consuming scoring requiring human raters—implies the risk that it may not be easily applied by the scientific community and practitioners. In this commentary, we outline important next steps building on the PISA assessment to further enhance future assessments of creative thinking. Crucial future directions include 1) determining what tasks and scorings ensure high psychometric quality including content validity, 2) enabling efficient, objective scoring by applying AI methods such as Large Language Models (LLMs), 3) ensuring high language accessibility via multilingual tests, 4) targeting a broader age group, and 5) facilitating standardized, reproducible assessments via an open online testing platform. In sum, these developments would lead to an efficient, validated multilingual test of creative thinking, which enhances the accessibility of effective creative thinking assessments and thereby supports the democratization and reproducibility of creativity research.

In order to rectify the historical marginalization of Black workers in computing fields, many academic and industrial initiatives have been established to increase the diversity and inclusion in the tech industry. In this study, we explored how one particular post-secondary education program at one historically black institution known as the Google in Residence (GIR) program impacted students' interests and their pursuit of computing-related careers. Data on employment outcomes at this institution showed that the GIR participants who obtained internships and full-time employment at Google were predominantly international students, not African American students who make up the majority of the undergraduate student and about half of the GIR participants. To understand this phenomenon better, we interviewed 27 students who spanned all 4 years of study and included African American and international students. The interviews were structured to elicit a wide range of factors influencing career decisions. Our analysis describes the impact of a particular GIR introductory-level programming course and other GIR program impacts beyond the introductory-level course. We found that the GIR introductory course was engaging, inspired students to change their degree in a more computing-oriented direction and supported internship applications. The informational workshops, networking events, mock-interviews, and advising of the computer science club, which were supported by the GIR program, built students' confidence in interviewing and obtaining full-time employment within the tech industry. While the GIR course and program had a positive influence on students of all backgrounds, the reputation of Google was especially motivating for international students. However, the African American students in this study generally had career aspirations and goals that were less tied to specific companies or industries. Based on our findings, potential improvements could include broadening awareness and access of the GIR course to non-computer science majors, offering summer programs to increase students' computational confidence, and increasing the diversity of GIR and computer science instructors.

Complex cognition, such as creativity, relies on cognitive integration of various component processes (e.g., memory, attention, and imagery). Yet, current methods cannot fully capture how the brain integrates cognitive processes during complex tasks. Previous research suggests that communication between functionally dissimilar regions might underlie cognitive integration, allowing for complex cognition. Here, we provide a formal test of this notion using task-based fMRI (n = 28) to assess functional connectivity (FC) among sets of regions ("levels") varying in their functional dissimilarity (defined by differences in resting-state FC profiles) across five tasks hypothesized to vary in cognitive complexity. Each task involved conceptual association and/or idea generation. We found that as task complexity increased, task-FC between regions with greater functional dissimilarity also increased, and the strength of this linear trend positively predicted the relative complexity of tasks. Thus, more complex tasks recruited greater interactions between functionally dissimilar regions. Furthermore, this effect was primarily driven by the default mode and frontoparietal control networks, especially connector hubs within these networks. Task-FC at the highest functional dissimilarity levels was most related to metaphor production and bi-association (involving integrating two concepts), followed by generating novel object uses and uncommon association (involving expanding one concept), and was least related to common association (thus, this task was the least complex). Altogether, task-FC across functional dissimilarity levels robustly tracked the cognitive complexity of tasks, supporting the validity of this neural feature for measuring cognitive complexity in a continuous manner and for data-driven tests of theorized differences in task complexity.

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 Undergraduate and graduate students need professional development skills to form expertise applicable to any job or future career. Mentoring is a way that students can learn how to engage in professional development. Likewise, students can learn professional development skills from mentors who they look to for expanding their knowledge base. To help address the needs of undergraduate and graduate students in engineering, the principal investigator developed and facilitated the Mentoring and Professional Development in Engineering Education (MPD-E2) Program. For this study, we examined the program's general functions and elements using session notes and discussion of our observations. The guiding research question for this study is: what are some elements of a mentoring and professional development program that students value? In this work, we present details about the elements of the program that support student development and insights about potential future opportunities for these types of programs.

Metaphor is crucial in human cognition and creativity, facilitating abstract thinking, analogical reasoning, and idea generation. Typically, human raters manually score the originality of responses to creative thinking tasks - a laborious and error-prone process. Previous research sought to remedy these risks by scoring creativity tasks automatically using semantic distance and large language models (LLMs). Here, we extend research on automatic creativity scoring to metaphor generation - the ability to creatively describe episodes and concepts using nonliteral language. Metaphor is arguably more abstract and naturalistic than prior targets of automated creativity assessment. We collected 4,589 responses from 1,546 participants to various metaphor prompts and corresponding human creativity ratings. We fine-tuned two open-source LLMs (RoBERTa and GPT-2) - effectively teaching them to score metaphors like humans - before testing their ability to accurately assess the creativity of new metaphors. Results showed both models reliably predicted new human creativity ratings (RoBERTa r = .72, GPT-2 r = .70), significantly more strongly than semantic distance (r = .42). Importantly, the fine-tuned models generalized accurately to metaphor prompts they had not been trained on (RoBERTa r = .68, GPT-2 r = .63). We provide open access to the fine-tuned models, allowing researchers to assess metaphor creativity in a reproducible and timely manner.

The standard definition of creativity as novel and useful describes creative products, but creativity is constituted by processes. This misalignment contributes to the oft-noted challenges of operationalizing creativity. Here, we distinguish creativity as a process from creativity as an attribute (i.e. creative-ness). Operating from a priori premises of creativity theory, we develop a process definition of creativity. Specifically, creativity is defined as internal attention constrained by a generative goal. This definition comprises three criteria: 1) attention is directed internally (toward mental representations); 2) attentional operations (e.g. search, manipulation) are constrained to fit parameters of a to-be-achieved goal state (whether or not a goal is actually achieved); and 3) the goal state is generative (not already precisely held in memory). We illustrate how these three definitional process elements align with insights yielded by creativity neuroscience, clarify ontological distinctions (e.g. from mind-wandering and retrieval), and relate the process definition to process-based models. The process definition provides minimal necessity and sufficiency criteria for whether a process should be considered creativity, but does not exclude the many other perceptual, emotional, etc. elements that can contribute to creativity processes. Researchers should specify whether they are studying creativity-as-process vs. creative-ness, and consider including process-focused assessments.

Overinclusive thinking, characterized by flexible category boundaries and broad associative networks, is closely linked to creativity. However, there has been a lack of rigorous psychometric evaluation of tasks measuring overinclusive thinking. In this paper, we introduce the Categorical Overinclusive Thinking Task (COverTT) and evaluate its reliability and validity. Across three studies involving 749 participants, we explore the relationship between overinclusive thinking, creativity, openness, creative behaviors, intelligence, and schizotypy. Our findings demonstrate that the COverTT is a reliable tool for assessing overinclusive thinking. Furthermore, we discuss the relationship between the COverTT and the criterion validity measures. To enable other researchers to readily use the COverTT for measuring overinclusive thinking, we provide open access to our data, code, and materials at OSF (https://osf.io/c3phq/?view_only=2973ca020429414db1ea069ede02bed5).

Creative divergent thinking involves the generation of unique ideas by pulling from semantic memory stores and exercising cognitive flexibility to shape these memories into something new. Although cognitive abilities decline with age, semantic memory tends to remain intact. This study aims to utilize that memory to investigate the effectiveness of a brief cognitive training to improve creative divergent thinking. Older adults were trained using a semantic retrieval strategy to improve creativity in the Alternate Uses Task (AUT) and the Divergent Association Task (DAT). Participants were tested on the AUT and DAT across three time points: before the strategy was introduced (T0 and T1) and afterward (T2). Results showed that the strategy enhances idea novelty in the AUT; additionally, participants that initially scored lowest on the AUT showed the greatest increase in AUT performance. This finding suggests that older adults can use a semantic retrieval strategy to enhance creative divergent thinking.

The role of top-down control in divergent creativity remains heavily debated. An outstanding question about the state dynamics of creativity concerns acute shifts between heightened and lowered creative states. Particularly, do transitions between creative states incur a switch cost as observed in other domains of cognition? Prior research showed that asymmetric switch costs are often incurred such that reaction time is asymmetrically slower when participants switch from a task involving more top-down control to a task involving less top-down control. We tested the hypothesis that frequent acute transitions from creativity-cued responding (associated with heightened creative state) to uncued responding (associated with lowered creative state) would incur an asymmetric switch cost such that uncued responding would be disproportionately impacted by state changes. We utilized the thin slices verb generation task in a task-switching paradigm. Consistent with the hypothesis of asymmetric switch costs in shifts between creative states, we observed a substantial switch cost when switching from creativity-cued trials to uncued trials, but no switch cost when switching from uncued trials to creativity-cued trials. These findings provide indirect evidence that heightened creative states may require substantially more top-down control than lowered creative states, supporting the theory that divergent creativity requires increased top-down control.