After reviewing the module resources and the readings, complete the following assignment. If necessary, consult additional resear

Şahin, Cogent Education (2016), 3: 1218315 http://dx.doi.org/10.1080/2331186X.2016.1218315

PROFESSIONAL EDUCATION & TRAINING | RESEARCH ARTICLE

General intelligence, emotional intelligence and academic knowledge as predictors of creativity domains: A study of gifted students Feyzullah Şahin1*

Abstract: Creativity of the individual is dependent on numerous factors, such as knowledge, general intelligence and emotional intelligence. The general pur- pose of this study is to investigate the effect of general intelligence, emotional intelligence and academic knowledge on the emerging of domain-specific cre- ativity. The study was conducted on 178 intellectually gifted students who at- tend high school. As a result of the study, correlations were determined between the scholarly creativity domains and sociability, global emotional intelligence (TEQ), science course, verbal and performance intelligence scores; mechani- cal/scientific creativity and mathematics and science courses, well-being and self-control; performance creativity and sociability; self/everyday creativity and science courses, well-being, self-control, sociability and global TEQ; artistic cre- ativity and sociability, and global TEQ. Moreover, researcher used a hierarchical regression analysis to see whether independent variants predict the creativity domains or not.

Subjects: Behavioural Management; Creativity; Gifted & Talented

Keywords: creativity domains; general intelligence; emotional intelligence; academic knowledge; gifted students

*Corresponding author: Feyzullah Şahin, Faculty of Education, Department of Gifted Education Division, Duzce University, Duzce, Turkey E-mails: [email protected], [email protected]

Reviewing editor: John Lee, Hong Kong Institute of Education, Hong Kong

Additional information is available at the end of the article

ABOUT THE AUTHOR Feyzullah Şahin is an assistant professor in the Department of Gifted Education Division, The University of Duzce, Turkey. He is currently the director of the master program for gifted education at Duzce University. The researcher has completed projects such as scientific creativity among the gifted students, the mentorship in the education of the gifted students in the mixed education environments, mentorship in developing creative thinking abilities, and socio-emotional needs of gifted students. His main research interest includes assessment of giftedness, gifted teacher education, mentoring, emotional intelligence of giftedness and creativity. His works on these issues have appeared in Turkish Journal of Giftedness and Education, Education and Science, Thinking Skills and Creativity, etc.

PUBLIC INTEREST STATEMENT Does creativity emerge generally or domain– specifically? Namely; could Thomas Edison, Architect Great Sinan or Picasso who became prominent with their creative products in various fields present creative products in the fields except their own fields? To what extent the knowledge, intelligence and emotional intelligence levels of the aforementioned individuals play a role in the field they study? Such questions are rather difficult to give straight answers. In this study the aim is to investigate the effect of general intelligence, emotional intelligence, and academic achievement on the emerging domain-specific creativity. As results, it is determined that the relationship between emotional intelligence sub-component and general intelligence sub-score and knowledge level and creativity sub-domains .

Received: 19 February 2016 Accepted: 26 July 2016 Published: 09 August 2016

© 2016 The Author(s). This open access article is distributed under a Creative Commons Attribution (CC-BY) 4.0 license.

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Feyzullah Şahin

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1. Introduction Many contemporary theories related to intelligence and creativity have been proposed in the litera- ture and are constantly being substituted for earlier ones. Students are at the center of interest for creativity, since they have skills for both inference and their position and they have creativity, emo- tions and interpersonal skills. The results of the research, which are related to some factors affecting creativity, are given below under subtitles.

1.1. General creativity vs. domain creativity Does creativity emerge generally or is it domain–specific? Can people produce works creatively, like Thomas Edison, Beethoven, or Picasso in the artistic domains or does the opposite situation occur? The natural and sexual selection burden in the developmental strengths (such as genetic drift and recombination) has been predominant in predisposing the human mind toward certain kinds of sen- sations and functions. These functions are distinct structures and domains that solve distinct problems.

There is much evidence for both the domain specificity and generality arguments. The general creativity point of view posits that there are creative individuals in one domain, who should be able to exhibit their creativity across other domains and that a general intellectual ability affects the performance of the individual (e.g. Hocevar, 1980; Torrance, 2008). However, creativity researchers started to shift from the traditional view of creativity in general toward the domain specific point of view. Gardner (1983) indicated that the cognitive function should be considered as being composed of a number of factors, with each factor functioning with regard to its own set of rules. An activity or process may occur in more than one mental domain (Karolyi, Ramos-Ford, & Gardner, 2003). He declared that outstanding responses were connected to specific domains that were involved with different kinds of skills and distinct types of knowledge. In this regard, domain-specific creativity studies used different tasks, such as writing stories and poems (Baer, 2003; Baer, Kaufman, & Gentile, 2004; Han, 2003) or storytelling (Baer, 1994), mathematics or word problems (Han, 2003; Sak & Ayas, 2013), musical compositions (Hickey, 2001) and collage making (Baer, 1994, 1996). However, the results of research on whether creativity is domain-specific or not, are contradictory. In a group of studies, the domain–specificity of creativity was supported (As for, Baer, et al., 2004; Hickey, 2001), while contradictory results were obtained from another group of studies (Conti, Coon, & Amabile, 1996; Eunsook & Milgram, 2010).

1.2. Intelligence–creativity The relationship between creative ability and intelligence can be explained by the threshold theory. According to this theory, both concepts are related, but the relationship between the two is not lin- ear across different levels of intelligence (Jauk, Benedek, Dunst, & Neubauer, 2013). In a meta-ana- lytic study conducted by Kim (2005), who used 21 studies, it was reported that the empirical findings did not support the threshold hypothesis. In a study by Şahin (2014), which examined the threshold effect and employed seven experimental research papers, it was reported that the results of three of them supported the theory, while four did not.

Some studies, which analyzed the relationship ignoring the aforementioned theory, could not detect a correlation between creativity and intelligence (e.g. Plucker, 2010; Richmond, 1966; Yoon, 2005). Moreover, Şahin (2015) and Wallbrown, Wallbrown, and Wherry (1975) reported that a high degree of separation was evident between these constructs. The relationship between divergent thinking and cognitive competencies was analyzed within the context of general intelligence (g factor) and fluent intelligence. In those studies, correlations were determined between divergent thinking and general intelligence and (r = .34, .21, and .12; Batey, Chamorro-Premuzic, & Furnham, 2009; Silvia, 2008; Furnham, 2015; respectively) and fluent intelligence (r = .43, .26 and .21; Batey et al., 2009; Batey, Furnham, & Safiullina, 2010; Virgolim, 2005, respectively).

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1.3. Emotional intelligence–creativity The root of TEQ can be dated back to the term of “social intelligence”, which was developed by Thorndike (1920), to refer to the ability to understand and manage people and to act wisely in hu- man relationships. Its direct roots lie in Gardner’s study on multiple intelligences, more categorically, in his terms of intrapersonal and interpersonal intelligence (Petrides, 2011). Petrides (2011) found that emotional intelligence structures could be comprehended as a trait of emotional intelligence (TEQ), about emotion-related self-perceptions and ability emotional intelligence about emotion-re- lated cognitive abilities. Thus, TEQ influences, directly or indirectly, a very wide range of variables in creativity thinking skills.

Creativity thinking skills may emerge as both potential and performance factors. There are two basic criteria for creativity potential. They are divergent thinking and the personal traits of the indi- vidual (see meta-analysis by Feist, 1998; see review by Sak, 2009). In this study, the potential dimen- sion of creativity was considered. The individuals with high levels of creativity differed from their peers from the point of their personality traits, too (e.g. Clayton & Snelbecker, 2007). Among the eighty-three studies on scientific and artistic creativity, a positive correlation was found between extraversion, openness and neuroticism, while a negative correlation was found between agreea- bleness and conscientiousness in a meta-analysis study (Feist, 1998). In another meta-analysis, which included 12 studies, in which the creativity personality traits of the individuals whose fields of interest were measured using the Big Six Interests by Larson, Rottinghaus, and Borgen (2002) were compared to the Big Five Personality traits. Significant correlations were found between artistic and openness (r = .48), enterprising and extraversion (r = .41), social and extraversion (r = .31), investiga- tive and openness (r = .28), and social and agreeableness (r = .19). In a longitudinal study, which took 45 years and was conducted on 163 males by Soldz and Vaillant (1999), a positive affinity with open- ness was determined (r = .40); while a negative relation was determined with adaptability (r = –.27). They could not find any correlation that was determined in the other three personality traits.

Sánchez-Ruiz, Hernández-Torrano, Pérez-González, Batey, and Petrides (2011) determined posi- tive and significant correlations between creative personality traits and extraversion and openness. Moreover, negative, significant and slight correlations were determined between the Torrance think- ing creativity test (TTCT) (figural form) total score and self-control (r = –.10), positive, significant and slight correlations were determined with sociability (r  =  .03), and insignificant relations with well- being, emotionality and global TEQ. In addition to this, Şahin, Özer, and Deniz (2016) determined positive and significant correlations between sociability and scholarly mechanic/scientific perfor- mance and art creativity domains (r = .24, .13, .21, .31, and .14, respectively) and self/everyday crea- tivity and well-being, self-control, emotionality and global TEQ (r  =  .14, .19, .23, .31, and .28, respectively). No significant correlation was determined among the other dimensions.

1.4. Knowledge–creativity Creativity is accepted to be a domain for general everyday skills and it develops into domain specific forms upon the acquisition and utilization of domain relevant skills and knowledge (Amabile, 1996). In the process of general creativity, common sense knowledge, which is simple, general and rela- tively unstructured, plays a major role. In contrast, in domain-specific creativity, domain specificity and technical knowledge is the foundation of creativity (Ayas & Sak, 2014). Thus, a “deep explora- tion” approach suggests that the originality of generated ideas is dependent on the degree to which people engage in deep exploration of their knowledge (Rietzschel, Nijstad, & Stroebe, 2007).

Amabile (1983) also stated:

Knowledge organized according to general principles is of greater utility than specific, narrowly applicable collections of facts. Likewise, performance information organized according to general approaches to problems, rather than blind response algorithms, should be more likely to contribute to high levels of creativity … an increase in domain–

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relevant skills can only lead to an increase in creativity, provided that the domain–relevant information is organized appropriately … that larger stores of properly coded knowledge increase the probability of outstanding responses.

Ward (2008) found that the stored domain-specific information tends to be used extensively while developing a domain-specific product and 69% of the individuals used the old domain-specific infor- mation while developing an original product. Academic achievement is an important criterion in evaluating academic knowledge. The literature reveals numerous studies on the correlation be- tween academic achievement and creativity. Some studies indicated the correlation between crea- tivity and academic achievement (Bolindifar & Noordin, 2013; Powers & Kaufman, 2004), but some studies could not find a correlation (Candrasekaran, 2013; Olatoye, Akintunde, & Ogunsanya, 2010). In another study, which included 18 research papers conducted between 1960 and 1990, analyzed the correlations between academic achievement and creativity. A correlation was found in seven of them, while no correlation was determined in eight of them. In three studies, a correlation was de- termined between the abilities of divergent thinking and productivity, which are necessary for high academic achievement (Ai, 1999).

1.5. Present study Affective and cognitive processes may influence creative abilities. Affective processes have been investigated in studies, which have indicated that gifted and talented students may have different characteristics from their peers, such as personal differences, like a drive for achievement, willing- ness to exert themselves, perseverance, thirst for knowledge and inventiveness (Heller, 1991), also having emotional intensity (Chan, 2000; Terman & Oden, 1976), having advanced levels of feelings of humor and esthetics, they are into their independency (Endepohls-Ulpe & Ruf, 2005) and are in- ternally motivated (Chan, 2000).

It was found in a meta-analysis that gifted students had more extravert characteristics (51.30%), intuition (71.60%), thinking (53.80%) and perceiving (60.10%) personality traits than their peers (Sak, 2004). In addition to this, the result of the Munich Giftedness longitudinal study indicated that gifted students had better intelligence, creativity, social competence, artistic (musical), and psycho- motor ability domains than their non-gifted peers (Heller, 1991). There is a large volume of available literature, which states that they differ from their peers in their creativity levels (e.g. Preckel, Holling, & Wiese, 2006; Runco, Millar, Acar, & Cramond, 2010; Şahin, 2014; Sligh, Conners, & Roskos-Ewoldsen, 2005) and their capacity for information processing.

On the other hand, the assessment and evaluation experts suggested that each group should be evaluated independently from the others, since the data, which was collected from some subgroups during the research, had values that were different from the general average (Hair, Hult, Ringle, & Sarstedt, 2014). When the aforementioned theoretical aspects and the findings of research sum- marized above are considered, the domain-specific creativity of the gifted students might differ from their peers, thus, it would be better to establish the study group with the gifted students only.

There are numerous studies, which are related to the determination of general intelligence, emo- tional intelligence, academic success and the correlations between them. However, there is only one study, which analyzed the correlations between the aforementioned variants and scholarly, me- chanic/scientific, performance, self/everyday and art creativity domains.

Gardner (1983) stated that cognition function should be accepted as being composed of several factors, where each factor functions according to its own set of rules. He expressed that exceptional responses were related to specific domains that required different kinds of skills and specific types of knowledge. On the other hand, different suggestions were made in various studies, which were related to the principles that should be formed according to creativity domains (Feist, 2004) or the number of the existing domains (e.g. Carson, Peterson, & Higgins, 2005; Kaufman & Baer, 2004a, 2004b; Kaufman, Evans, & Baer, 2010; Oral, Kaufman, & Agars, 2007; Rawlings & Locarnini, 2007).

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Kaufman (2012) suggested the creativity domains, which were analyzed in the study. Scholarly crea- tivity would reflect Ivcevic and Mayer’s (2009) intellectual creativity, Feist’s (2004) linguistics and Gardner’s (1999) linguistic intelligence. Mechanical/scientific creativity would cover Gardner’s logi- cal—mathematical and naturalistic intelligences, Ivcevic and Mayer’s intellectual creativity, and Carson et al. (2005) science factor. Performance includes Gardner’s bodily kinesthetic and musical intelligence, Ivcevic and Mayer’s performance arts and Feist’s music. Self/everyday creativity would cover Gardner’s ideas of interpersonal and intrapersonal intelligence and Ivcevic and Mayer’s crea- tive lifestyle. The art creativity theoretical framework would be Gardner’s spatial intelligence, Carson and colleagues’ art factor, and Feist’s art.

The general purpose of this study was to investigate the effect of general intelligence (verbal, performance and index score), emotional intelligence (well-being, self-control, emotionality, socia- bility and global TEQ), and academic achievement (mathematics and science scores and grade point average) on the emerging of domain-specific creativity (scholarly, mechanic/scientific, performance, self/everyday and art). The answers will be sought for the following questions, within the context of this general purpose:

(1) Is there any significant correlation between general intelligence, emotional intelligence, aca- demic achievement of the gifted students and their domain-specific creativity?

(2) Does the general intelligence, emotional intelligence and academic achievement of the gifted students significantly predict their domain-specific creativity?

2. Method

2.1. Participants The study was conducted on 178 intellectually gifted students who attend high school during the educational year of 2014–2015 and who fill the measurement instruments wholly and completely and whose intelligence scores and academic achievement grades were obtained completely. The students of the aforementioned school have the scores of +2 Sd or higher in at least one of WISC–R IV verbal, performance or index scores. Moreover, they were determined to be free of adaptive and behavioral problems during their enrolling to the school. Among the students, 85 of them (47.75%) were female (22 of them at the ninth grade, 21 of them at the tenth grade, 17 of them at the elev- enth grade and 25 of them at the twelfth grade) while 93 of them (52.25%) were male (28 of them at the ninth grade, 19 of them at the tenth grade, 20 of them at the eleventh grade and 26 of them at the twelfth grade).

2.2. Measures

2.2.1. Kaufman domains of creativity scale (KDOCS–TR) The scale developed by Kaufman (2012) was adapted into Turkish culture by Şahin (2016). As a result of the adaptation process, a structure with five factors, which the structure in the original scale with 42 items was preserved, emerged. The scale is assessments according to self-evaluation method. The scale is in five-point Likert form. The scores to be obtained from sub-dimensions are as follows; 5–55 for creativity, 7–35 for mechanic/ scientific, 9–45 for artistic performance and self/ everyday, 5–25 for art domain, and 42–201 for total scale. As a result of the confirmatory factor analysis (CFA), the fit indices of the model were above the average (χ2/df = 1.94, GFI = .78, CFI = .93, RMSEA = .06, and SRMR = .07). The internal consistency reliability coefficient of KDOCS–TR was determined as .87 for the sub-factor of scholarly creativity, .84 for mechanical/scientific, .86 for performance, .77 for self/ everyday, .83 for artistics, and .90 for total. In this study, KDOCS sub-dimensions are computed between .78 and .86.

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2.2.2. Emotional intelligence specialty scale–short form (TEQ–SF) TEQ–SF is a scale developed by Petrides and Furnham (Petrides & Furnham, 2000, 2001) based on the conceptualization of emotional intelligence as “the trait of personal character” in order to determine self perception levels of the individuals related to their emotional sufficiency. The scale was adapted into Turkish culture by Deniz, Özer, and Işık (2013). As a result of adaptation, a structure with 20 items and four factors was established. The fit indices confirm the validity of the structure (χ2/ df = 2.46, GFI = .95, AGFI = .92, CFI = .91, RMSEA = .056, and SRMR = .060). The internal consistency reliability coefficient of TEQ–SF was found .72 for well-being, .70 for self-control, .66 for emotionality, .70 for sociability and .81 for the whole while test–repeat test reliability coefficient was found .86 (Deniz et al., 2013). In this study, TEQ–SF sub-dimensions Cronbach’s alpha internal consistency co- efficient values are computed between .60 and .67.

2.2.2.1. Wechsler intelligence scale for children–R IV (WISC–R IV). The notion that one-dimension- al intelligence is a measurement tool provided a basis for the development of WISC–R. Wechsler developed it in 1949 and revised in 1974. The test was complied to Turkish by Savaşır and Şahin (1994, cit. Tan, Soysal, Aldemir, & Işık, 2012) for 6–16 age group. Split half-test reliability was calcu- lated as .97 for index score. It was found that there was a correlation between sub-tests between .51 and .86. WISCR–IV Guttman split-half reliability was determined as .87.

2.2.2.2. Academic achievement grades. The academic knowledge levels of the students were eval- uated within the context of academic achievement grades. Grade point average score was calcu- lated from the average of grades from the courses of science, mathematics, literacy, ethics, social science, arts and the optional courses. The grades were calculated through the system of 100. The grade point average and science courses’ Guttman split-half reliability was computed as .82, and .86, respectively.

2.2.3. Procedure KDOCS and TEQ–SF were applied to the students who were voluntary in the evening courses. The results of the intelligence tests are the results of individual results of the tests conducted while their application for enrolling the school. Academic achievement scores are the grades obtained at the end of autumn term in the 2014–2015 education years. Both scores were obtained from the school administration.

2.2.4. Data analysis The data, which was obtained from the participants, was transferred to the computer and analyzed using the SPSS (16.00) statistical analysis software program. The data-set was primarily evaluated in terms of missing values and normality assumptions. Accordingly, no missing value was observed, while the normal distribution assumptions of Kurtosis and Skewness coefficients were found. In seeking for answers to the first sub-question of the study, Pearson’s correlation test was employed and the analysis of the forward method multiple hierarchical regression was used for the second sub-question. In the regression analysis, the VIF and Tolerance coefficients for the sub-fields of scholarly, mechanical/scientific, performance, self/everyday and art creativity were determined as 1.014–.986, 1.041–.961, 1.009–.991, 1.042–.875, and 1.009–.991, respectively. These results indicate that there are no multiple linear relationships among the independent variants.

3. Results

3.1. Descriptive statistics and correlations Mean, standard deviation, Cronbach’s alpha internal consistency coefficients and Pearson’s correla- tions for all variables in this study are presented in Table 1. Significant and positive correlations were observed between scholarly and sociability, global TEQ, science course, WIS–R IV verbal and perfor- mance (r = .41, and .20, p < .01; r = .15, .18, and .16, p < .05, respectively); Mechanical/scientific and mathematics and science course scores, well-being and self-control (r = .11, .25, p < .05; r = .17, and .25, p < .01, respectively); Performance and sociability (r = .23, p < .01; r = .17, p < .05, respectively);

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self/ everyday and science course scores, well-being, self-control, sociability and global TEQ (r = .20, .34, .05, .33, and .28, p < .01, respectively); art and sociability and global TEQ (r = .26, and .20, p < .01). On the other hand, a significant and negative correlation was determined between mechanical/sci- entific and emotionality (r  =  –.18, p  <  .05), performance and art and mathematics course scores (r = –.17 –.20, p < .05).

3.2. Multiple regressions To examine the extent to which general intelligence, emotional intelligence, course scores and grade point average scores could predict variance in creativity subdomains, a series of forward

Table 1. Descriptive statistics, reliability and Pearson inter—correlation for all measures

Note: N = 178. *p < .05. **p < .01.

    M SD α 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 KDOCS 1. Schol-

arly 39.32 7.82 .86 – .12 .38** .44** .40** .08* –.06 .09 .08 .09 .07 .41** .20** .18* .16* .02

2. Me- chani- cal/sci- entific

21.92 6.83 .86   – .05 .30** .41** .11* .25* .11 .17** .25** –.18* .01 .14 .02 .05 .09

3. Perfor- mance

30.01 8.40 .85     – .30** .30** .12 –.17* –.06 .11 .04 –03 .23** .08 .01 –.10 .02

4. Self/ every- day

33.57 5.97 .78       – .34** .20** .05 –.15 .34** .05** –.03 .33** .28** .11 .06 .06

5. Art 17.32 4.92 .81         – –.02 –.20* –.06 .11 .07 .13 .26** .20** –.05 .12 .05

Course scores

6. Sci- ence

84.12 7.92 –           – .60** .81** .15* –.01 –.06 .01 .18* .03 .09 .04

7. Math- ematic

78.08 14.48 –             – .79** .12 .12 –.10 –.10 .02 .05 –.05 –.03

8. Grade point average

83.87 6.58 –               – .17* .02 –.06 –.01 .12 .09 .01 .01

TEQ–SF 9. Well- being

19.12 4.44 .62                 – .13 –.05 .29** .32** –.01 .13 .09

10. Self- control

15.69 3.62 .61                   – .15* .16* .19** .03 .01 .13

11. Emo- tionality

15.47 3.71 .60                     – .24** .15 –.07 .12 .04

12. So- ciability

17.88 3.79 .67                       – .41** –.08 .09 .01

13. Global EQ

16.94 3.78 .63                         – –.06 .10 .03

WISC–R IV

14. Verbal

123.68 5.63 –                           – –.07 .56**

15. Perfor- mance

134.57 7.25 –                             – .69**

16. Index score

132.28 4.72 –                               –

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method multiple hierarchical regressions were performed. Therefore, WISC–R were the verbal, the performance, and the index scores, TEQ were the well-being, self-control, emotionality, sociability and global TEQ scores, course scores of the science and mathematics courses, and the grade point averages were regressed onto each of the five di

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