Studies of creativity have advanced extensively over the past several decades (Runco and Abdullah, 2014). Initially, creativity was tied to the arts; for example, only artists were thought to be creative. Although this view persists in the form of an art bias (Cropley, 2014; Runco, 2014), it is widely held that creativity can be expressed in diverse domains (Gardner, 1983; Runco, 1986). The term domain has been defined as “the set of representations that underlie and support thinking in a specific area of knowledge” (Baer, 2011, p. 404). Evidence largely supports domain specificity, meaning that an individual who is creative in one domain is not necessarily creative in other domains.

Empirical demonstrations of domain specificity often use some form of a Creative Activity and Accomplishment Checklist (CAAC). The CAAC is highly praised; after a thorough review, Hocevar and Bachelor (1989) described it as the best method for measuring creativity. An advantage of the CAAC is that it provides domain-specific scores. Originally proposed by Chorness and Nottelmann (1957) and then extended and refined by Holland (1961) and Holland and Richards (1965), the CAAC has demonstrated good reliability in a variety of studies. Holland (1961) used the CAAC to demonstrate that extracurricular activity is not strongly related to academic success. Wallach and Wing (1969) used a CAAC in their research, showing that students’ school performance is not strongly related to creativity expressed when students are outside of school, which has been recently replicated by Runco et al. (2023) in a study that also used a version of the CAAC. Paek and Runco (2018) reported an ideational contribution to certain domains of creative activity. They also developed two new scales for the CAAC—one representing technological creativity and the other for everyday creativity. They also proposed a new scoring system to assess the quality of creative accomplishment. Paek et al. (2016) reviewed all research to date that has used some form of the CAAC.

One empirical investigation provided a modicum of validity for the CAAC (Runco et al., 1990). The self-ratings of students were significantly correlated with mothers’ reports of students’ creative activities and accomplishments. The students received one version of the CAAC, while the mothers received a parallel version, allowing them to describe the activities and accomplishments of their own children.

Previous studies with the CAAC have largely supported domain specificity; however, the newest form has new domains: technology and everyday creativity. Thus, it would make sense to replicate previous work with a new version of the CAAC. Additionally, newer versions provide both the quantity of activity and quality of accomplishment scores. Runco (1986) had a qualitative scoring method for the CAAC; however, it required judges and was thus open to subjectivity. Newer CAACs have an objective method of obtaining qualitative scores—another reason to replicate earlier work with a new version of the checklist.

The new method of qualitative scoring in the CAAC makes it possible to test for polymathy among students. Polymathy is an exception to domain-specific creativity. Polymathy occurs when an individual performs creatively in more than one domain. Root-Bernstein et al. (1995) reported that in a sample of Nobel Prize winners and members of the US National Academy of Science, the 11 individuals representing the highest level of eminence reported using their avocations in their professions. Twelve individuals in the same sample reported that the avocations were a waste of time. Thus, polymathy is not universal among eminent individuals. Another testable hypothesis is that creative polymathy is observed only in mature samples, which makes sense, given the benefits of avocations for professional efforts. Root-Bernstein and Root-Bernstein (2023) asked whether creative polymathy is found only among the eminent and questioned the need for the creative polymath to be productive. In this context, productivity appears to be a feature of professional life.

The CAAC can test for polymathy among students because it measures the quantity and quality of creative activity. The quantity of creative activities within a domain can be used as a proxy for what mature creators do avocationally. If it is an avocation, there is probably little social recognition, which is exactly what distinguishes the quality and quantity scores on the CAAC. The CAAC quality scores, contrastingly, can be used as a proxy for the professional work of mature creators, for here, there is social recognition. In sum, mature creators invest time in avocations, which sometimes actually contribute to the professional creativity that earns them social recognition; and here we tested this sort of thing by correlating the quantity of creative activity in one domain on the CAAC with the quality of creative accomplishment in other domains measured by the CAAC.

This investigation was not just a replication of the previous reports of domain specificity. It extends previous research by checking domain specificity with the CAAC, which includes new domains of creative activity. Additionally, we tested our conception of polymathy among students. Given the possibility that polymathy requires above-average talent, the sample for this research comprised both gifted and non-gifted students. In sum, this investigation was conducted to test for polymathy among students, compare gifted and nongifted students in this regard, and to determine statistically if what holds for mature creators (a relationship of quantity and quality of creative activity) is also apparent among adolescents.

The internal consistency was calculated for each CAAC domain. The reliability coefficients ranged from 0.73 to 0.91 (Table 1).

There are several notable results of the analyses. The correlations in Table 6, for example, largely suggest domain specificity. The highest bivariate correlation among domains in the gifted sample was 0.71, and the highest in the non-gifted sample was 0.61. The former indicates that 50% of the variance in the domain scores was shared, while the latter indicates that 37% of the variance was shared. Notably, the highest correlation was between Crafts and Everyday Creativity; two domains where overlap is expected. Some domains were negligibly correlated (e.g., 0.072 and 0.085). Of course, domain specificity is not all-or-nothing but a matter of degrees.

The percentage results (Table 2) also mostly supported domain specificity. Only 29 of the 306 students (90% or above) excelled in two or more domains. These percentage results, as well as the regression analysis results, indicate that the degree that various domains are correlated tends to depend on giftedness status. One tentative conclusion is that domain specificity is the norm; however, some polymaths do well in more than one domain (cf. Table 8).

The regression analyses using the separate domains, with the quantitative CAAC scores as predictors and quality of creative accomplishment as criteria, were consistent with Simonton’s (2003) constant probability of success model. Briefly, the logic here is that the more one does (quantity), the more likely it is that something of high quality will be discovered. If students write 100 poems (Writing domain), ceteris paribus, they are more likely to produce an award-winning poem than those who write only one.

The results of the last set of regression analyses indicate that participating in creative activities, even in other domains, can predict qualitative achievement (social recognition) in different domains. This may be the clearest form of support for polymathy. Recall here that polymathy in eminent samples is apparent when the individual has some creative avocation but also performs at an excellent level in a different domain—Einstein’s practice of the violin while changing the field of physics can be cited here. In this investigation, working in some avocations with no professional expectations was operationalized concerning the quantity of activity. Professional achievement, meanwhile, is more strongly related to the quality of one’s creative accomplishments.

This study used the CAAC to assess the quality and quantity of creative performance. The CAAC has been used for many years (e.g., Holland and Richards, 1965; Wallach and Wing, 1969; Paek and Runco, 2018) and is highly respected (Hocevar and Bachelor, 1989). Still, it is a self-report; thus, it is open to certain biases (e.g., memory and honesty). One study reported correlations between children’s CAAC reports and those of their mothers, implying a mild form of validation (Runco et al., 1990). In this investigation, reliabilities were quite good. Future research could extend this line of work by testing other domains or perhaps by adding controls for the limitations such as memory and honesty. Runco et al. (2014) developed a lie scale for the Runco Ideational Behavior Scale, and a similar scale can be written into the CAAC. The variance attributed to dishonesty could then be controlled, and polymathy analyzed. Future research might examine polymathy among students with a version of the CAAC that only includes domains which have been found in adult polymaths, for more focus, but with more questions within each domain for more information. Future research should certainly replicate this study using other samples. The present sample was homogeneous and perhaps not informative about countries and cultures other than the one sampled. Further, the present investigation had imbalanced group sizes, and although hierarchical regression is not sensitive to this sort of thing, it could be avoided if there is a replication or extension. Additional research might also collect data to determine why certain domains were associated with one another (e.g., technology and writing) and what, if anything, in participants’ developmental histories contributed to polymathy. Additional CAAC domains might be examined in the future, as well.

There are varying kinds of polymathy and different approaches to studying it. Some research focused on skill, ability, knowledge, or worldviews (e.g., Sriraman, 2009; Araki, 2018). Future research could explore if these variables help explain the differences (gifted vs. non-gifted) and associations among the domains uncovered here. Additionally, Root-Bernstein and Root-Bernstein (2020a) described a kind of intra-domain polymathy that bridges (rather than separates) domains. Indeed, quite a few eminent individuals are famous for their work within one domain, but in actuality, their thinking is borrowed from more than one domain (Gardner and Wolf, 1988). Such individuals are polymaths in their thinking but not in their performance. That being said, polymathy is not always constrained by domain boundaries. The research reported here only examined trans-domain polymathy. Root-Bernstein and Root-Bernstein (2020b, p. 377) distinctions between limited, proper, serial, and passive polymaths, one key question for us was, are (trans-domain proper) polymaths only found among eminent samples, or do we see them among gifted students? Based on the data reported here, the answer is that this particular kind of polymath is apparent among gifted students.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by Directorate of Scientific Research, Ministry of Education, Bahrain. The studies were conducted in accordance with the local legislation and institutional requirements. Written informed consent for participation in this study was provided by the participants’ legal guardians/next of kin.

AMA: Methodology, Software, Validation, Writing – review & editing. MAR: Conceptualization, Methodology, Project administration, Writing – original draft. AEA: Data curation, Formal analysis, Validation, Writing – review & editing.