Creativity research commonly involves recruiting human raters to judge the originality of responses to divergent thinking tasks, such as the alternate uses task (AUT). These manual scoring practices have benefited the field, but they also have limitations, including labor-intensiveness and subjectivity, which can adversely impact the reliability and validity of assessments. To address these challenges, researchers are increasingly employing automatic scoring approaches, such as distributional models of semantic distance. However, semantic distance has primarily been studied in English-speaking samples, with very little research in the many other languages of the world. In a multilab study (N= 6,522 participants), we aimed to validate semantic distance on the AUT in 12 languages: Arabic, Chinese, Dutch, English, Farsi, French, German, Hebrew, Italian, Polish, Russian, and Spanish. We gathered AUT responses and human creativity ratings (N= 107,672 responses), as well as criterion measures for validation (e.g., creative achievement).We compared two deep learning-based semantic models—multilingual bidirectional encoder representations from transformers and cross-lingual language model RoBERTa—to compute semantic distance and validate this automated metric with human ratings and criterion measures. We found that the top-performing model for each language correlated positively with human creativity ratings, with correlations ranging from medium to large across languages. Regarding criterion validity, semantic distance showed small-to-moderate effect sizes (comparable to human ratings) for openness, creative behavior/achievement, and creative self-concept. We provide open access to our multilingual dataset for future algorithmic development, along with Python code to compute semantic distance in 12 languages. © 2023 American Psychological Association

Scoring divergent thinking tasks opens multiple avenues and possibilities-decisions researchers have to make. While some scholars postulate that scoring should focus on the best ideas provided, the measurement of the best responses (e.g., top scoring) comes along with challenges. More specifically, compared to the average quality across all responses, top scoring uses less information-the bad ideas are thrown away-which decreases reliability. To resolve this issue, this article introduces a multidimensional top-scoring approach analogous to linear growth modeling which retains information provided by all responses (best ideas and bad ideas). Across two studies, using both subjective human ratings and semantic distance originality scoring of responses to over a dozen divergent thinking tasks, we demonstrated that Maximum (the best idea) and Top2 Scoring (two best ideas) could surpass typically applied average scoring in measurement precision when the bad ideas' originality is used as auxiliary information (i.e., additional information in the analysis). We thus recommend retaining all ideas when scoring divergent thinking tasks, and we discuss the potential this new approach holds for creativity research and practice.

The associative theory of creativity has long held that creative thinking involves connecting remote concepts in semantic memory. Network science tools have recently been applied to map the organization of concepts in semantic memory, and to study the link between semantic memory and creativity. Yet such work has largely overlooked the domain of convergent thinking, despite the theoretical importance of semantic memory networks for facilitating associative processes relevant for convergent problem solving (e.g., spreading activation). Convergent thinking problems, such as the Compound Remote Associates (CRA) test, can be solved with insight (the sudden aha experience) or analysis (deliberately and incrementally working towards the solution). In a sample of 477 participants, we adopted network science methods to compare semantic memory structure across two grouping variables: 1) convergent thinking ability (i.e., CRA accuracy), and 2) the self-reported tendency to solve problems with insight or analysis. Semantic memory networks were constructed from a semantic fluency task, and problem solving style (insight or analysis) was determined from judgments provided during solving of CRAs. We found that, compared to the low-convergent thinking group, the high-convergent thinking group exhibited a more flexible and interconnected semantic network-with short paths and many connections between concepts. Moreover, participants who primarily solved problems with insight (compared to analysis) showed shorter average path distances between concepts, even after controlling for accuracy. Our results extend the literature on semantic memory and creativity, and suggest that the organization of semantic memory plays a key role in convergent thinking, including insight problem solving.

Creativity has long been conceptually linked to experiences of emotion and mind wandering, yet these empirical relationships remain unclear, and few studies have explored the thoughts and emotions of creative people in daily life. To investigate how creativity relates to everyday cognitive and affective experiences, the present study (N = 159) used experience sampling to examine how creative cognition (divergent thinking ability) and creative behavior (self-reported creative activity and achievement) measured in the lab may predict thought content, affective state, and the frequency of mind wandering (i.e., task-unrelated thought) in daily life. Additionally, we assessed in-the-moment thoughts and emotions predictive of thinking about a creative project in everyday life (i.e., creative project thought ). We found that each form of creativity was generally associated with positively-valenced experiences, such as having pleasant thoughts, enjoying one's everyday activities, and feeling motivated and inspired. We also found that positive, activating emotions (happy and energetic) were positively associated with divergent thinking ability and in-the-moment creative project thought. Furthermore, positive, deactivating emotions (relaxed and connected) negatively predicted momentary creative project thought-indicating that positive affect can be tied to less creative thinking, depending on the activation level of emotions. No relationship was found between daily-life mind wandering frequency and divergent thinking ability or creative behavior/achievement, suggesting that the overall amount of task-unrelated thought in everyday life is not related to individual creativity. Taken together, the present findings provide novel evidence on the everyday experiential correlates of creative thinking and behavior.