Search for: All records

Abstract Metaphor generation is both a creative act and a means of learning. When learning a new concept, people often create a metaphor to connect the new concept to existing knowledge. Does the manner in which people generate a metaphor, via sudden insight (Aha! moment) or deliberate analysis, influence the quality of generation and subsequent learning outcomes? According to some research, deliberate processing enhances knowledge retention; hence, generation via analysis likely leads to better concept learning. However, other research has shown that solutions generated via insight are better remembered. In the current study, participants were presented with science concepts and descriptions, then generated metaphors for the concepts. They also indicated how they generated each metaphor and rated their metaphor for novelty and aptness. We assessed participants’ learning outcomes with a memory test and evaluated the creative quality of the metaphors based on self‐ and crowd‐sourced ratings. Consistent with the deliberate processing benefit, participants became more familiar with the target science concept if they previously generated a metaphor for the concept via analysis compared to via insight. We also found that metaphors generated via analysis did not differ from metaphors generated via insight in quality (aptness or novelty) nor in how well they were remembered. However, participants’ self‐evaluations of metaphors generated via insight showed more agreement with independent raters, suggesting the role of insight in modulating the creative ideation process. These preliminary findings have implications for understanding the nature of insight during idea generation and its impact on learning. 

ABSTRACT We investigated the oscillatory brain processes while people generated metaphors for science concepts. Applying a hidden Markov model, we extracted brain states, representing temporally disentangled oscillatory processes, from EEG data. By associating the trial‐by‐trial occupancy of brain states with the creative quality, novelty, and aptness of the generated metaphors, we identified oscillatory processes that played a role in creative ideation in a data‐driven manner. Metaphor novelty was positively associated with occupancy in a state featuring widespread alpha‐band synchronization during the early trial stage and occupancy in a state featuring alpha‐band desynchronization during the later trial stage. In addition, metaphor novelty was negatively associated with gamma‐band power. Our results not only extend previous literature on the role of oscillatory processes in creative ideation but also highlight the importance of temporal dynamics in understanding the brain mechanisms during sustained cognitive task performance. 

Creativity research often relies on human raters to judge the novelty of participants’ responses on open-ended tasks, such as the Alternate Uses Task (AUT). Albeit useful, manual ratings are subjective and labor intensive. To address these limitations, researchers increasingly use automatic scoring methods based on a natural language processing technique for quantifying the semantic distance between words. However, many methodological choices remain open on how to obtain semantic distance scores for ideas, which can significantly impact reliability and validity. In this project, we propose a new semantic distance-based method, maximum associative distance (MAD), for assessing response novelty in AUT. Within a response, MAD uses the semantic distance of the word that is maximally remote from the prompt word to reflect response novelty. We compare the results from MAD with other competing semantic distance-based methods, including element-wise-multiplication—a commonly used compositional model—across three published datasets including a total of 447 participants. We found MAD to be more strongly correlated with human creativity ratings than the competing methods. In addition, MAD scores reliably predict external measures such as openness to experience. We further explored how idea elaboration affects the performance of various scoring methods and found that MAD is closely aligned with human raters in processing multi-word responses. The MAD method thus improves the psychometrics of semantic distance for automatic creativity assessment, and it provides clues about what human raters find creative about ideas. 

Many people have claimed that sleep has helped them solve a difficult problem, but empirical support for this assertion remains tentative. The current experiment tested whether manipulating information processing during sleep impacts problem incubation and solving. In memory studies, delivering learning-associated sound cues during sleep can reactivate memories. We therefore predicted that reactivating previously unsolved problems could help people solve them. In the evening, we presented 57 participants with puzzles, each arbitrarily associated with a different sound. While participants slept overnight, half of the sounds associated with the puzzles they had not solved were surreptitiously presented. The next morning, participants solved 31.7% of cued puzzles, compared with 20.5% of uncued puzzles (a 55% improvement). Moreover, cued-puzzle solving correlated with cued-puzzle memory. Overall, these results demonstrate that cuing puzzle information during sleep can facilitate solving, thus supporting sleep’s role in problem incubation and establishing a new technique to advance understanding of problem solving and sleep cognition.