Creative fluency and originality are pivotal indicators of creative potential. Both have been embedded in hierarchical intelligence models as part of the ability to retrieve information from long-term memory; an ability that is often measured with indicators of retrieval fluency. Creative fluency and retrieval fluency, both expressed by the count of correct responses, are procedurally highly similar. This raises the question how creative fluency and originality are related with retrieval fluency and how both are predicted by other cognitive abilities. In a multivariate study (N = 320), we found that retrieval fluency is very strongly related with creative fluency (r = .87) and substantially related with originality (r = .59). A combined fluency factor still fitted the data well. Cognitive abilities accounted for 63% variance in fluency and 47% variance in originality. After controlling for established cognitive abilities, latent variables for fluency and originality were unrelated with one another. This suggests that the procedural proximity of the ability to fluently generate either information from long-term memory or ad-hoc solutions to unusual tasks and the ability to come up with original ideas needs reconsideration. Locating originality below an overarching retrieval factor is contradicted by the present data.
{"title":"How Much Retrieval Ability Is in Originality?","authors":"Selina Weiss, Benjamin Goecke, Oliver Wilhelm","doi":"10.1002/jocb.659","DOIUrl":"10.1002/jocb.659","url":null,"abstract":"<p>Creative fluency and originality are pivotal indicators of creative potential. Both have been embedded in hierarchical intelligence models as part of the ability to retrieve information from long-term memory; an ability that is often measured with indicators of retrieval fluency. Creative fluency and retrieval fluency, both expressed by the count of correct responses, are procedurally highly similar. This raises the question how creative fluency and originality are related with retrieval fluency and how both are predicted by other cognitive abilities. In a multivariate study (<i>N</i> = 320), we found that retrieval fluency is very strongly related with creative fluency (<i>r</i> = .87) and substantially related with originality (<i>r</i> = .59). A combined fluency factor still fitted the data well. Cognitive abilities accounted for 63% variance in fluency and 47% variance in originality. After controlling for established cognitive abilities, latent variables for fluency and originality were unrelated with one another. This suggests that the procedural proximity of the ability to fluently generate either information from long-term memory or ad-hoc solutions to unusual tasks and the ability to come up with original ideas needs reconsideration. Locating originality below an overarching retrieval factor is contradicted by the present data.</p>","PeriodicalId":39915,"journal":{"name":"Journal of Creative Behavior","volume":"58 3","pages":"370-387"},"PeriodicalIF":2.8,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jocb.659","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140964408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Benjamin Goecke, Paul V. DiStefano, Wolfgang Aschauer, Kurt Haim, Roger Beaty, Boris Forthmann
Automated scoring is a current hot topic in creativity research. However, most research has focused on the English language and popular verbal creative thinking tasks, such as the alternate uses task. Therefore, in this study, we present a large language model approach for automated scoring of a scientific creative thinking task that assesses divergent ideation in experimental tasks in the German language. Participants are required to generate alternative explanations for an empirical observation. This work analyzed a total of 13,423 unique responses. To predict human ratings of originality, we used XLM-RoBERTa (Cross-lingual Language Model-RoBERTa), a large, multilingual model. The prediction model was trained on 9,400 responses. Results showed a strong correlation between model predictions and human ratings in a held-out test set (n = 2,682; r = 0.80; CI-95% [0.79, 0.81]). These promising findings underscore the potential of large language models for automated scoring of scientific creative thinking in the German language. We encourage researchers to further investigate automated scoring of other domain-specific creative thinking tasks.
{"title":"Automated Scoring of Scientific Creativity in German","authors":"Benjamin Goecke, Paul V. DiStefano, Wolfgang Aschauer, Kurt Haim, Roger Beaty, Boris Forthmann","doi":"10.1002/jocb.658","DOIUrl":"10.1002/jocb.658","url":null,"abstract":"<p>Automated scoring is a current hot topic in creativity research. However, most research has focused on the English language and popular verbal creative thinking tasks, such as the alternate uses task. Therefore, in this study, we present a large language model approach for automated scoring of a scientific creative thinking task that assesses divergent ideation in experimental tasks in the German language. Participants are required to generate alternative explanations for an empirical observation. This work analyzed a total of 13,423 unique responses. To predict human ratings of originality, we used XLM-RoBERTa (Cross-lingual Language Model-RoBERTa), a large, multilingual model. The prediction model was trained on 9,400 responses. Results showed a strong correlation between model predictions and human ratings in a held-out test set (<i>n</i> = 2,682; <i>r</i> = 0.80; CI-95% [0.79, 0.81]). These promising findings underscore the potential of large language models for automated scoring of scientific creative thinking in the German language. We encourage researchers to further investigate automated scoring of other domain-specific creative thinking tasks.</p>","PeriodicalId":39915,"journal":{"name":"Journal of Creative Behavior","volume":"58 3","pages":"321-327"},"PeriodicalIF":2.8,"publicationDate":"2024-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jocb.658","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140976304","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Ahmed M. Abdulla Alabbasi, Mark A. Runco, Maha S. Almutairi, Alaa Eldin A. Ayoub
Previous research suggests that environment can play an important role in encouraging or discouraging creative expression and productivity. Additional research has uncovered a discrepancy between the creativity students express at school and the creativity they express outside of school. The fact that, in previous research, students expressed more creativity outside of school than when in school implies that school discourages creativity. So far, the creativity gap has only been studied with nongifted students. One objective of the present investigation was to check for a similar discrepancy among gifted learners. Four hundred and eighty-seven middle school and high school students from the State of Kuwait (240 gifted and 247 nongifted) were recruited. The Creativity Activities and Accomplishment Checklist (CAAC) was administered to compare students' creative activities at home and school. The primary finding of this investigation was that the strength of the relationship between creativity at home and creativity at school differed in gifted and nongifted students. What was called a creativity gap existed in both groups, but it was smaller in the gifted group. A second finding was that gifted students expressed more creativity at school compared with the nongifted group, in particular CAAC domains. There were no differences between the gifted and the nongifted groups in the creativity expressed at home, except for one subscale, namely everyday creativity. Although gifted students expressed more creativity at school, compared with their nongifted peers, they were nonetheless more creative at home compared with school. Finally, hierarchical regression analyses indicated that measure of personality significantly moderated the relationship between creativity at home and creativity at school. Limitations and future directions are discussed.
{"title":"Is Creativity Expressed at Home Related to Creativity Expressed at School? A Re-Examination of the Creativity Gap with Gifted and Nongifted Students","authors":"Ahmed M. Abdulla Alabbasi, Mark A. Runco, Maha S. Almutairi, Alaa Eldin A. Ayoub","doi":"10.1002/jocb.656","DOIUrl":"10.1002/jocb.656","url":null,"abstract":"<p>Previous research suggests that environment can play an important role in encouraging or discouraging creative expression and productivity. Additional research has uncovered a discrepancy between the creativity students express at school and the creativity they express outside of school. The fact that, in previous research, students expressed more creativity outside of school than when in school implies that school discourages creativity. So far, the creativity gap has only been studied with nongifted students. One objective of the present investigation was to check for a similar discrepancy among gifted learners. Four hundred and eighty-seven middle school and high school students from the State of Kuwait (240 gifted and 247 nongifted) were recruited. The <i>Creativity Activities and Accomplishment Checklist</i> (CAAC) was administered to compare students' creative activities at home and school. The primary finding of this investigation was that the strength of the relationship between creativity at home and creativity at school differed in gifted and nongifted students. What was called a creativity <i>gap</i> existed in both groups, but it was smaller in the gifted group. A second finding was that gifted students expressed more creativity at school compared with the nongifted group, in particular CAAC domains. There were no differences between the gifted and the nongifted groups in the creativity expressed at home, except for one subscale, namely everyday creativity. Although gifted students expressed more creativity at school, compared with their nongifted peers, they were nonetheless more creative at home compared with school. Finally, hierarchical regression analyses indicated that measure of personality significantly moderated the relationship between creativity at home and creativity at school. Limitations and future directions are discussed.</p>","PeriodicalId":39915,"journal":{"name":"Journal of Creative Behavior","volume":"58 3","pages":"356-369"},"PeriodicalIF":2.8,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jocb.656","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929030","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Alisa Scherbakova, Denis Dumas, Selcuk Acar, Kelly Berthiaume, Peter Organisciak
Creativity can be assessed using various methods, including divergent thinking performance, self-ratings, and teacher ratings. However, these measures may not always align, as they may not consistently identify creative potential in the same manner. The present study aimed to identify latent subgroups of students based on their observed originality, creative self-efficacy, teacher-rated originality, academic achievement in reading and mathematics, and demographic background characteristics. Data were collected from 243 elementary school students. We applied the normal mixture technique to classify participants into latent subgroups. Five latent subgroups of students were identified: Overconfident Low Performers, Creative High Achievers, Under-Confident Below-Average Achievers, Mathematically Oriented Students, and Calibrated Above-Average Achievers. Female students tended to fall disproportionately into the subgroup of Creative High Achievers. Students receiving free/reduced lunch had a lower probability of being Creative High Achievers. Special education students had a higher probability of falling into the subgroup Overconfident Low Performers. Teacher ratings of students' originality were more in line with student academic performance rather than with their performance-based originality scores. Students' self-ratings of creativity bifurcated across subgroups, with Creative High Achievers and Overconfident Low Performers reporting the highest self-ratings of originality, despite displaying very different levels of performance on the divergent thinking assessment.
{"title":"Performance and Perception of Creativity and Academic Achievement in Elementary School Students: A Normal Mixture Modeling Study","authors":"Alisa Scherbakova, Denis Dumas, Selcuk Acar, Kelly Berthiaume, Peter Organisciak","doi":"10.1002/jocb.646","DOIUrl":"10.1002/jocb.646","url":null,"abstract":"<p>Creativity can be assessed using various methods, including divergent thinking performance, self-ratings, and teacher ratings. However, these measures may not always align, as they may not consistently identify creative potential in the same manner. The present study aimed to identify latent subgroups of students based on their observed originality, creative self-efficacy, teacher-rated originality, academic achievement in reading and mathematics, and demographic background characteristics. Data were collected from 243 elementary school students. We applied the normal mixture technique to classify participants into latent subgroups. Five latent subgroups of students were identified: Overconfident Low Performers, Creative High Achievers, Under-Confident Below-Average Achievers, Mathematically Oriented Students, and Calibrated Above-Average Achievers. Female students tended to fall disproportionately into the subgroup of Creative High Achievers. Students receiving free/reduced lunch had a lower probability of being Creative High Achievers. Special education students had a higher probability of falling into the subgroup Overconfident Low Performers. Teacher ratings of students' originality were more in line with student academic performance rather than with their performance-based originality scores. Students' self-ratings of creativity bifurcated across subgroups, with Creative High Achievers and Overconfident Low Performers reporting the highest self-ratings of originality, despite displaying very different levels of performance on the divergent thinking assessment.</p>","PeriodicalId":39915,"journal":{"name":"Journal of Creative Behavior","volume":"58 2","pages":"245-261"},"PeriodicalIF":3.9,"publicationDate":"2024-05-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jocb.646","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140929032","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Autistic traits are found throughout the general population, but their link to creative attributes has received little attention in childhood populations. In adults, autistic traits are linked to both creative benefits and disadvantages, moderated by the autistic trait and the creative domain under investigation. The current study investigates the link between autistic traits and creative attributes (creative personality traits, creative talent, creative artistic choices) in children aged 10–14 years. Autistic traits were measured using the Adolescent-AQ, both globally (AQ-Total) and for individual subscales (AQ-Attention to detail, AQ-Imagination, and “AQ-Core”, i.e., combining AQ-Social skills, AQ-Attention switching, AQ-Communication). Using child and parent reports, data from 149 children revealed an association between autistic traits and creative personality traits (both positive and negative) while also showing a (weaker) relationship with creative artistic choices. Global and core autistic symptoms negatively predicted creative personality traits. At the same time, AQ-Imagination predicted lower creative attributes across nearly all creative domains. Finally, and in contrast, AQ-Attention to detail positively predicted a number of creative attributes (i.e., creative personality traits, creative talent). Our results show how autistic traits map to a range of creative attributes, across children in the general population.
{"title":"Are Children with Autistic Traits More or Less Creative? Links between Autistic Traits and Creative Attributes in Children","authors":"Rebecca Smees, Julia Simner, Louisa J. Rinaldi","doi":"10.1002/jocb.650","DOIUrl":"10.1002/jocb.650","url":null,"abstract":"<p>Autistic traits are found throughout the general population, but their link to creative attributes has received little attention in childhood populations. In adults, autistic traits are linked to both creative benefits and disadvantages, moderated by the autistic trait and the creative domain under investigation. The current study investigates the link between autistic traits and creative attributes (creative personality traits, creative talent, creative artistic choices) in children aged 10–14 years. Autistic traits were measured using the Adolescent-AQ, both globally (AQ-Total) and for individual subscales (AQ-Attention to detail, AQ-Imagination, and “AQ-Core”, i.e., combining AQ-Social skills, AQ-Attention switching, AQ-Communication). Using child and parent reports, data from 149 children revealed an association between autistic traits and creative personality traits (both positive and negative) while also showing a (weaker) relationship with creative artistic choices. Global and core autistic symptoms negatively predicted creative personality traits. At the same time, AQ-Imagination predicted lower creative attributes across nearly all creative domains. Finally, and in contrast, AQ-Attention to detail positively predicted a number of creative attributes (i.e., creative personality traits, creative talent). Our results show how autistic traits map to a range of creative attributes, across children in the general population.</p>","PeriodicalId":39915,"journal":{"name":"Journal of Creative Behavior","volume":"58 3","pages":"328-341"},"PeriodicalIF":2.8,"publicationDate":"2024-04-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/jocb.650","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140670251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"心理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}