Masterthesis E. Bekker-Janssens [4254694]

1 Running head: INTELLIGENCE, CREATIVITY AND LITERACY ABILITY

The role of divergent thinking and convergent thinking in the relation between

intelligence and literacy ability

Masterthesis

Universiteit Utrecht

Masteropleiding Pedagogische Wetenschappen

Masterprogramma Orthopedagogiek

Name: E. Bekker-Janssens

Student number: 4254694

Supervisor: dr. E.H. Kroesbergen

Second supervisor: dr. J.H. van de Beek

Date: 17-6-2015

Number of words: 3.662


Voorwoord

Allereerst wil ik jou bedanken, Evelyn, voor alle tijd, ruimte en feedback die je me hebt

gegeven. Steeds opnieuw wist je me richting te geven zonder te sturen. Ik ben tevreden over

het eindresultaat en heb van het proces genoten.

Jan, bedankt voor het kritisch mee- kijken en denken. Lotte, Eveline, Sanne en Lisanne, dank

voor de fijne samenwerking bij het afnemen van alle tests en het scoren van de schrijftaken.

Oma Rita, bedankt voor al die keren dat Abel gezellig met Ties mocht spelen als ik uurtjes

tekort kwam. Bedankt lieve Anne, Evelien, Marijke, Marieke, Marion Mariette en Steffie. Ik

was een vreselijk nalatige zus /dochter /vriendin de afgelopen periode, maar jullie bleven

onverminderd begripvol.

En dan mijn mannen: Martijn, Stijn, Mees en Abel. Het was vast niet altijd leuk, mama achter

de laptop aan de keukentafel, bedolven onder artikelen, krabbels en boeken. Toch heb ik mij

van het begin af aan door jullie gesteund gevoeld in dit proces. Zonder woorden, maar

weldegelijk. Ik wil jullie daar ongelofelijk voor bedanken. Bedankt!

Peirce means "conceivable" very broadly. It allows any flight of imagination, provided this

imagination ultimately alights upon a possible practical effect; and thus many hypotheses

may seem at first glance to be excluded by the pragmatical maxim that are not really so

excluded.


Abstract

The aim of this study was to get more in depth information as to why gifted children are

vulnerable to underachieving and low well-being. Based on preliminary research, it was

hypothesized that this might have to do with larger discrepancies between divergent and

convergent thinking above IQ 120, greater variability of academic performance and possible

relations between the two. It was expected that illuminating these relations might provide us

with essential information about the functioning of gifted children. For this purpose, 458

Dutch children from 12 regular primary schools participated in intelligence- and creativity

tests. Also scores of Dutch standardized literacy tests were taken into account. Based on

literature study and factor analysis, 6 variables were computed: intelligence, convergent

creativity (abstraction component), convergent creativity (innovation component), divergent

creativity, word reading and reading comprehension. Data were analysed using Kendall’s

Tau-B correlation and one-way between groups analysis of variance (ANOVA). It was found

that creative abstraction correlates positively with intelligence below the threshold, whereas

creative innovation only starts correlating above IQ 120. Discrepancies between convergent

and divergent creativity (convergent > divergent) were confirmed to be higher above the

threshold, as well as the variability between literacy scores. Discrepancies with divergent

thinking exceeding convergent thinking showed positive correlations with reading

comprehension. Possible explanations and suggestions for future research are being discussed.

Key words: intelligence, creativity, divergent thinking, convergent thinking, literacy

ability, underachieving, threshold theory, compensation theory, facilitation theory.


The role of divergent thinking and convergent thinking in the relation between intelligence

and literacy ability

Intelligence is the capacity to think logically and solve problems in novel situations,

independent of acquired knowledge (Cattell, 1963). Children with both high intelligence and

high creativity levels are referred to as being ‘gifted’ (Renzulli, 1986). Intelligence is known

to be a strong predictor of academic performance (Hansenne & Legrand, 2012). Yet, being

gifted is associated with underachieving (Kroesbergen, Van Hooijdonk, Middel-Lalleman,

Rijnders, & Van Viersen, 2015; Mann, 2006; Whitmore, 1980, cited in McCoach & Siegle,

2003) and low levels of well-being (Kroesbergen et al., 2015). This phenomenon can partly be

explained by the fact that our educational system is poorly adapted to the needs of gifted

children (Preckel, Gotz, & Frenzel, 2010). Educational fit and proper support are known to be

necessary conditions for gifted children to reach their full potential (Subotnik & Rickoff,

2010). This doesn’t explain though, why it is the gifted and not the highly intelligent child

that is underachieving and suffering from low well-being. Creativity seems to be of influence

on the relation between intelligence and academic performance. Yet, little is known about the

relation between these variables (Subotnik, Olszewski-Kubilius, & Worrell, 2011). The aim of

this study is to contribute to an increased insight in the relation between intelligence,

creativity and literacy ability in both gifted and non-gifted children.

Divergent and convergent thinking in the creative cognitive process

In studying the relation between intelligence, creativity and literacy ability it is

important to distinguish between divergent and convergent thinking (Barbot, Besencon and

Lubart, 2011; Cropley, 2006). Divergent thinking refers to the ability to view an idea from

different angles leading to various creative ideas. Divergent tasks are process-based and

focused on the quantity of a production. Divergent thinking is positively related to creative

potential (Runco & Acar, 2012) and can be measured by divergent thinking tests. The act of

combining various heterogeneous elements into a unique, original production refers to

convergent-integrative thinking (Barbot, 2011). Convergent-integrative tasks imply a product-

based approach, focusing on the quality of the production and leading to creative achievement

(Runco & Acar, 2012). In the current study, creativity is referred to as a cognitive process

consisting of both divergent and convergent thinking.

The relation between intelligence and creativity

Some research has shown that creativity test scores are independent from IQ scores,

whereas other research has confirmed a relationship between the two (Kim, 2005). According

to the threshold theory a positive linear correlation between intelligence and creativity is


present up to a certain point, usually IQ 120 (Jauk, Benedek, Dunst, & Neubauer, 2013). From

thereon up, the correlation between intelligence and creativity is said to be weak or absent

(Yamamoto, 1964a). The threshold theory has been extensively studied, with contradictory

and inconclusive results (Runco & Albert, 1986). This inconsistency may come from different

measures for creativity. Jung and colleagues (2009) provided neurobiological support for a

critical “threshold” regarding the relationship between intelligence and creativity, as measured

with divergent thinking tests. However, contemporary research shows that the breaking point

depends on the operationalization of the construct creativity. Quantitative criteria measure

divergent thinking, whereas qualitative criteria measure convergent thinking. It has been

found that quantitative criteria will lead to a lower breaking point than qualitative criteria

(Benedek, Franz, Heene, & Neubauer, 2012; Karwowski & Gralewski, 2013). Based on the

work of Benedek and collegues (2012) and Karwowski and collegues (2013), it could be

deduced that discrepancies between divergent and convergent thinking might be larger in

gifted than in non-gifted children.

Figure 1. Threshold theory: significant correlations between creativity and intelligence below

the threshold (IQ = 120), with correlations above the threshold being weak or absent.

Literacy ability

In the Netherlands, primary schools mainly focus on two domains: mathematics and

literacy ability. Literacy ability consists of the sub-domains vocabulary, reading and spelling.

Two main skills in reading are word reading and reading comprehension (Oakhill & Chain,

2007). Word reading contains two fundamental aspects: decoding and automating. Once a

child is able to view each letter as a separate unit that corresponds to a particular sound, it can


learn to merge the sounds into words (Stanovich, 1986). Then, the child can be taught to

recognize combinations of letters. This is called automating (Perfetti, 1985). Word reading is

a necessary condition for reading comprehension (Clarke, Snowling, Truelove, & Hulme,

2010), which is the process of interacting with and giving meaning to a text (Bruner, 1985).

Literacy ability in gifted and non-gifted children

In the context of this research, literacy ability is particularly interesting because the

various subdomains seem to be differentially related to intelligence and creativity. With

regard to non-gifted children, strong positive correlations have been found between

intelligence and comprehensive reading (Stanovich, Cunningham & Freeman, 1984; Broos,

Fulker & De Vries, 1990), intelligence and vocabulary (Liegeois, Cross, Polkey, Harkness, &

Vargha-Khadem, 2008) and intelligence and word reading and spelling (Cornwall, 1992;

Strang, 1968). Positive correlations were also found between creativity and both reading

comprehension (Popov, 1992; Tien, Hsu, Tai, & Yang, 2014) and vocabulary (Al Issra, 1964).

Controversy exists about the relation between creativity and word reading and spelling.

Ritchie, Luciano, Hansell, Wright and Bates (2013) assessed reading, spelling and non word

repetition in a large sample, and studied associations with creativity. Based on the

compensatory theory, Ritchie and colleagues expected to find high creativity rates in children

with poor reading and spelling abilities. It was hypothesized that reading disability may

involve a compensatory cognitive benefit in the form of enhanced creativity (Chakravarty,

2009; Eide & Eide, 2011; Tafti, Hameedy, & Baghal, 2009). Yet, creativity was found to be

positively related to word reading and spelling, even when controlling for IQ (Ritchie et al.,

2013). These findings led to a novel theory: the theory of facilitation, which suggests that

fluency in written language may facilitate creative thought and curiosity (Ritchie et al., 2013).

In the current research, this theory of facilitation has been tested.

Little is known about the relation between intelligence, creativity and literacy ability in

gifted children. Based on the threshold theory, it could be hypothesized that above IQ 120

correlations between intelligence and creativity are weak or absent, and thus larger

discrepancies between divergent and convergent thinking are conceivable. Finch, Neumeister,

Burney and Cook (2014) examined 61 gifted preschoolers and found that, despite intelligence

quotient scores in the very superior range (IQ > 130), great variability was observed on word

reading and spelling, with means ranging from average to superior levels. Large discrepancies

between divergent and convergent thinking are thought to be negatively related to (academic)

achievement (Chermahini & Hommel, 2010; Cropley, 2006; Lubow & Gewirtz, 1995; Wolf

& Mieg, 2010). In the current research, this hypothesis will be tested.


Objectives and hypotheses

Based on the preliminary research, four hypotheses were formulated:

Hypothesis 1. Below the threshold (IQ = 120) intelligence and creativity correlate positively,

whereas above the threshold correlations are weak or absent.

Hypothesis 2. Discrepancies between divergent thinking and convergent thinking are larger

above than below the threshold (divergent > convergent).

Hypothesis 3. Variability in literacy ability scores is larger above than below the threshold.

Hypothesis 4. Discrepancies between divergent and convergent thinking (divergent >

convergent) are negatively related to literacy ability scores.

Method

Participants

458 Dutch pupils from 12 regular primary schools participated in intelligence- and

creativity tests, after active consent was obtained from their parents. The participants were

recruited from 26 classes in grade 4 (n = 311), grade 5 (n = 73) and grade 6 (n = 74). Pupils in

grade 4 were offered a screening for gifted education simultaneously, resulting in a relatively

big sample size. The total sample consisted of boys (52%) and girls (48%) in the age of 8-13

years. The average age was 9.92 years (SD = 0.88).

Instruments

Intelligence: Raven’s Standard Progressive Matrices has been used as a measure of

intelligence (Raven, Court, & Raven, 1992; Raven, 2000). Raven’s Standard Progressive

Matrices is a useful instrument to identify both high achievers and potential high achievers

who’s abilities have not yet fully developed (Kroesbergen et al.; 2015). In this study,

participants got 45 minutes to complete the task, the number of right answers was noted.

Abdel-Khalek (2005) found test-retest reliability ranging between .69 and .85 and Cronbach’s

alpha between .88 and .93.

Literacy ability: Literacy scores were retrieved from a national standardized

assessment, called CITO. This national literacy test consists of the items: spelling, reading

speed, reading comprehension and vocabulary. In the current research, the CITO literacy test

displayed Crohnbach’s alpha .523. To examine the underlying structure of the CITO literacy

scores more closely, data from all participants that had no missings on any of the literacy

measures (N=84) were subjected to principal axis factoring with varimax rotation. Two

factors were identified as underlying the four variables of the CITO literacy test. In total,


these factors accounted for 76% of the variance. Consequently, reading comprehension and

vocabulary were computed into one variable (referred to as: reading comprehension). The

other variable consisted of word reading and spelling (referred to as: word reading). Prior to

running the principal axis factoring, examination of the data indicated that most of the

variables were normally distributed and a linear relationship was identified among the

variables.

Creativity (divergent): Divergent thinking can be measured by the Torrance Test of

Creative Thinking (Torrance, Ball, & Safter, 2008). Test-retest reliabilities were reported in

the .60-.80 range (Haensly & Torrance, 1990). Since we chose to focus on literacy ability, the

verbal version of this test was selected (instead of the figural version). Activity 5 of the

verbal test showed good to excellent inter-rater agreement (fluency: kappa = .815, flexibility:

kappa = .710 and originality: kappa = .631) and good reliability (α = .841). To investigate the

underlying structure of the test, data collected from 458 participants were subjected to

principal axis factoring with varimax rotation. One factor (with Eigenvalue 2.61) was

identified, accounting for around 87% of the variance. Thus, the three variables (fluency,

flexibility and originality) were computed into a new variable, called: “divergent creativity”.

Given the robust nature of factor analysis and the fact that a linear relationship was identified

among the variables, the fact that variables were not perfectly normally distributed was

considered not to be problematic.

Creativity (convergent): The Creative Writing Task was a composition on a specific

topic, written by primary school children. The test had to be completed in 30 minutes and was

conducted in order to assess domain specific creative achievement. The Creative Writing Task

was designed by Tsai-Ling Chu and Wei-Wen Lin (2013). Chu and Lin (2013) have found the

inter-rater reliability correlation coefficients between two raters to be positive for technical

goodness (r = .67, p < .001) and creativity (r = .73, p < .001). In the current study, children

were not given a specific topic (sentence) but an image as an initial stimulus. The

Experimental Scoring Manual for Minnesota Tests for Creative Thinking and Writing

(Yamamoto, 1964b) was used by three raters to evaluate the creative writing products. On

each scale one item had to be deleted, due to the nature of our stimulus (visual instead of

verbal). To assess inter-rater agreement, Kappa was calculated for the remaining 24 items (6

scales, 4 items on each scale). Kappa scores varied between excellent (richness: .786;

originality: 1), good (sensitivity: .715; imagination: .742) and acceptable (organisation: .610;

psychological insight: .679). For the Creative Writing Task Crohnbach’s alpha was .652. To

investigate the underlying structure of the Creative Writing Task, data collected from 418


participants was subjected to principal axis factoring with varimax rotation. Prior to running

the principal axis factoring, examination of data indicated that the variables were not perfectly

normally distributed. Given the robust nature of factor analysis, these deviations were not

considered problematic. Furthermore, a lineair relationship was identified among the

variables. Two factors (with Eigenvalues exceeding 1) were identified as underlying the six

variables of the Creative Writing Task. In total, these factors accounted for around 53% of the

variance in the Creative Writing Task data. The first factor consisted of the variables:

sensitivity, imagination, richness and organisation. This factor was computed into a new

variable, called: “convergent creativity: abstraction”. The second factor consisted of:

originality, psychological insight and organisation, and was computed into the new variable:

“convergent creativity: innovation”.

Procedure

The current study was approved by the Ethics Committee of the Faculty of Social

Sciences of Utrecht University. For pupils to participate in this study, parental informed

consent was provided. The examination was divided over two days and consisted of –amongst

others- the following tests: Raven’s Standard Progressive Matrices [SPM], the Torrance Test

of Creative Thinking-Verbal [TTCT-V], and the Creative Writing Task [CWT]. These tests

were conducted in a class-wise manner by academic master students. SPM and TTCT-V were

introduced according to the guidelines. Then participants were given 45 minutes for the

completion of SPM and 30 minutes for the completion of TTCT-V. With regard to Creative

Writing Task, participants were offered a picture, showing either a Capricorn in the woods or

an old door with a key hole. Participants were asked to write a story about their picture in 30

minutes. In addition to these tests, the results of standardized literacy tests were retrieved

from teachers, offering information on the academic achievement of the participants with

regard to spelling, reading speed, vocabulary and reading comprehension. Also, teachers were

asked to select highly intelligent pupils as nominees for a gifted education programme. In

return, the school board was advised which pupils to select for gifted education.

Data-analysis

Raw scores were transformed into ratio-scores, so scores could be compared to each

other and separate groups could be formed based on percentile-scores. Children performing

within the top 10% on the intelligence test (percentile ≥ 90) were selected for the group

“gifted” (n = 33). The remaining group (percentile < 90) was labelled “non-gifted” (n = 271).

The assumptions of normality, linearity and homoscedasticity were assessed for each group

separately, and found not to be supported for the “gifted” group. A visual inspection of the


normal Q-Q and detrented Q-Q plots for each variable in the “non-gifted” group showed that

“comprehensive reading” was the only variable normally distributed, therefore Kendall’s Tau-

B correlation was selected to assess the size and direction of the linear relationship between

intelligence, creativity and literacy ability. One-Way-Between Groups Analysis of Variance

(ANOVA) was conducted to investigate: 1) if discrepancies between divergent and

convergent creativity differ between gifted and non-gifted children, 2) if the level of literacy

ability differs between gifted and non-gifted children. Discrepancies were calculated by

subtracting divergent creativity scores from convergent creativity scores. Inspection of

skewedness, kurtosis and Shapiro-Wilk statistics indicated that the assumption of normality

was not supported for each of the three conditions. Levene’s statistics was significant for

word reading F (1, 35) = 10.25, p = .003 and reading comprehension F (1, 33) = 4.63, p =

.039, but non-significant for intelligence, F (1, 41) = 2.67, p = .110, thus the assumption of

homogeneity of variance was violated.

Results

Descriptive Statistics

Table 1 shows the number of children being nominated by their teacher for the gifted

education program. Statistics for boys and girls are being compared, as well as the number of

nominations within the gifted and non-gifted group of children. Table 2 offers an overview of

the means, standard deviations and ranges of the intelligence and creativity test scores of

gifted and non-gifted children.

Table 1

Sex, age and teacher nominations of gifted and non-gifted children

Variable Non-gifted Gifted

n 394 45

nboys 201 28

nnominatedboys 51 18

ngirls 193 17

nnominatedgirls 27 6

Mean age (SD) 9.9 (.87) 10.2 (.96)

Note. n = sample size; SD = standard deviation; nboys = number of teacher nominated boys;

ngirls = number of teacher nominated girls


Table 2

Means, standard deviations and ranges of test scores of gifted and non-gifted children

Non-gifted Gifted

Mean SD Range Mean SD Range

Raven 72.4 10.9 30-89 93.2 2.9 89-100

Reading comp. 38.5 8.9 0-95 56.5 15.4 19-92

Word reading 77.5 15.2 52-98 78.6 14.2 42-97

TTCT-V 42.8 20.9 0-100 42.5 19.1 6-86

CWT Abstraction 60.9 19.4 7-100 68.1 14.9 33-100

CWT Innovation 57.6 17.6 0-100 63.2 17.0 27-100

Note. Raven = fluid intelligence; Reading comp. = reading comprehension + vocabulary;

Word reading = word reading + spelling; TTCT-V = divergent creativity; CWT Abstraction =

abstraction component of convergent creativity; CWT Innovation = innovation component of

convergent creativity.

Hypothesis 1

To assess the size and direction of the linear relationship between intelligence,

creativity and literacy ability, Kendall’s Tau-B correlation coefficients (r ) were calculated.

Below the threshold, small positive correlations were found between intelligence and the

abstraction component of convergent creativity, r(377) = .178, p < .001. Above the threshold,

the abstraction component of convergent creativity showed weak negative correlations with

intelligence, r (40) = -.100, p = .415. Between intelligence and the innovation component of

convergent creativity, correlations were weak for non-gifted, and small and positive for gifted

children, r(40) = .156, p = .201. Correlations between intelligence and divergent thinking

[TTCT-V] were weak, both above and below the threshold (table 3).

Hypothesis 2

Discrepancies between divergent and convergent creativity were assessed using one-

way between groups analysis of variance (ANOVA). The ANOVA was statistically significant,

both for the abstraction and innovation component of convergent creativity, indicating that

discrepancies between convergent and divergent creativity (convergent > divergent) are larger in

gifted than in non-gifted children, as expected. Although not significant, non-gifted children showed

larger discrepancies with divergent creativity exceeding convergent creativity (table 4).


Table 3

Kendall’s Tau-B correlation coefficients of gifted and non-gifted children

Raven CWT

abstraction

CWT

innovation

TTCT-V

Word

reading

Reading

comprehension

Raven

1 -.100 .156 -.062 .160 -.142

CWT

Abstraction

.178** 1 .277* .236* -.070 .146

CWT

Innovation

.056 .345** 1 .069 .138 .007

TTCT-V

.078* .114* -.012 1 .104 .162

Word

reading

.089* .101* .205** .076* 1 .182

Reading

comprehension

.270** .178** .104* .080* .209** 1

Raven = fluid intelligence; Reading comprehension = reading comprehension + vocabulary;

Word reading = word reading + spelling; TTCT-V = divergent creativity; CWT abstraction =

abstraction component of convergent creativity; CWT innovation = innovation component of

convergent creativity. Correlations for gifted children are presented above the diagonal, and

correlations for non-gifted children are presented below the diagonal. * p<.05 ** p<.01

Table 4

Discrepancies between divergent and convergent creativity in gifted and non-gifted children

Non-gifted Gifted ANOVA

n M SD n M SD F p η2

Abstract > Div

Innov > Div

Div > Abstract

362

362

89

17.4

13.9

17.4

25.7

26.9

14.5

35

35

3

26.7

23.0

12.2

20.4

23.9

3.4

5.2

3.7

.401

.023

.055

.528

.013

.009

4.43

Div > Innov 107 18.9 15.8 6 11.9 13.8 1.1 .293 .009

Note. Abstract = abstraction component of convergent creativity, Innov = innovation component of

convergent creativity, Div = divergent creativity


Hypothesis 3

In order to analyse the variability of literacy scores, means, standard deviations and

ranges of the various test scores were retrieved (table 5). In addition, a one-way between

groups analysis of variance (ANOVA) was conducted to examine if literacy ability scores

were different for gifted and non-gifted children. The ANOVA was statistically significant for

reading comprehension, F (1, 364) = 40.76, p < .000 , η2 = .101. The ANOVA was not

statistically significant for word reading and spelling.

Table 5

Variability in reading scores in gifted and non-gifted children

Non-gifted Gifted ANOVA

n M SD n M SD F p η2

Reading comp. 329 38.8 15.3 37 55.8 16.5 40.7 .000 .101

Word reading 341 75.9 11.9 33 78.2 14.5 1.05 .305 .002

Note. Reading comp. = reading comprehension + vocabulary; Word reading = word reading +

spelling

Hypothesis 4

Finally, the size and direction of the linear relationship between divergent-convergent

discrepancies and literacy ability was examined, using Kendall’s Tau-B correlation

coefficients (r ). Small positive correlations were found between discrepancies (divergent >

convergent) and reading comprehension, r(79) = .264, p = .001. No significant correlations

were found for convergent thinking exceeding divergent thinking.

Conclusion and discussion

In the current research it was confirmed that intelligence and convergent creativity

correlate positively below the threshold, yet correlations between intelligence and divergent

creativity were negligible. With regard to gifted children, correlations between intelligence

and creativity were absent for divergent creativity, as expected, yet small correlations were

found for the innovation component of convergent creativity. Below the threshold,

correlations for the innovation component were merely absent, indicating that the innovation

component of convergent creativity is only significant in gifted children (figure 4).


Figure 4. Correlations between intelligence and creativity above and below the threshold

As shown in figure 5, discrepancies (convergent > divergent) were found to be larger in

gifted children. Also variability in literacy scores was confirmed to be larger above the

threshold, as shown in figure 6 and 7. It was found that the mean scores of word reading were

similar below and above the threshold, whereas gifted children outperformed non-gifted

children with regard to reading comprehension.

Figure 5. Discrepancies between divergent and convergent creativity, both above and below

the threshold


Reading comprehension

Small correlations were found between reading comprehension and creative

discrepancies (divergent > convergent). In line with the theory of facilitation, the direction of

this correlation was positive, suggesting that a wide focus of attention may be useful in the

process of incorporating seemingly irrelevant and unrelated information to solve a problem or

gain more insight (Runco, 2004). Creative discrepancies (divergent > convergent) occurred

equally in gifted and non-gifted children, yet mean scores on reading comprehension were

higher for gifted children. Also the variability of the scores was significantly larger above the

threshold. This may be explained by the superior level of intelligence in gifted children,

which is associated with larger working memory capacity (Benedek, Jauk, Sommer,

Arendasy, Neubauer, 2014). Working memory is a primary resource for the control of

attention (Engle, 2002; Kane, Bleckley, Conway & Engle, 2001). It supports the active

maintenance of task-relevant information and the controlled search from memory (Unsworth

& Engle, 2007), which is highly relevant in reading comprehension. Yet, creativity is also

predicted by inhibition and personality factors (Benedek et al., 2014). Creative achievement

depends on an adaptive engagement of inhibition in order to repulse stimuli that are too

obvious or irrelevant and at the same time keep creative thought flowing (Vartanian, 2009;

Zabelina & Robinson, 2010). Gifted children seem to have more difficulty controlling

attention due to an active imagination and a propensity to daydream (Baum & Olenchak,

2002; Cramond, 1994b). This might explain the wide range of scores in reading

comprehension.

Figure 6. Means and variability in reading comprehension test scores, both above and below

the threshold


Word reading

The ability to narrow and sustain attention to information is needed for analytical tasks

or performing sequences of steps (like word reading). This can be more problematic for gifted

children, because of their varied interests (Baum & Olenchak, 2002; Cramond, 1994b). Strong

correlations were found between attention problems in gifted children and difficulty with

academic and preliteracy tasks like rapid automatized naming (Kiefer, & Martens, 2010).

Automaticity is traditionally thought to occur unconsciously and independent from top-down

control (Posner & Snyder, 1975; Schneider & Shiffrin, 1977). Yet, according to the

attentional sensitization model of unconscious cognition (Kiefer & Martens, 2010),

automaticity also strongly relies on controlled top-down activity (Beaty, Silvia, Nusbaum,

Jauk, & Benedek, 2014).

Figure 7. Means and variability in word reading test scores, both above and below the

threshold

Summarizing, it can be concluded that large working memory capacity, combined

with elevated levels of divergent thinking is associated with superior reading comprehension.

The combination of these characteristics is frequently present in gifted children (figure 6).

However, in order to properly master the basic elements of the reading process, children also

need to be able to narrow and sustain attention. With regard to word reading, gifted children

with good attention control seem to outperform non-gifted children, whereas word reading

scores of gifted children with attention problems appear to be dramatically lower than those of

non-gifted peers (figure 7). This suggests that the ability and/or motivation for adaptive


inhibition and top-down control, is a key element in the word reading process of gifted

children.

Limitations and future research

It must be noted that participants were not randomly selected, data were not all

normally distributed and the sample size of the group of gifted children was small (n = 45).

However, the total sample size was considerable (n = 440) and so was the amount of data

taken from participants. The Creative Writing Task (utilized to assess convergent creativity) is

an unconventional instrument; reliability and validity have not been formally reviewed.

Nevertheless, it seems to compliment former research on the threshold theory, which was

based on divergent creativity only (Benedek, Franz, Heene, & Neubauer, 2012; Karwowski &

Gralewski, 2013). In order to gain more insight in (extremely) gifted children, it might be

relevant to further explore the innovation component of convergent creativity in future

research. With regard to the current research, implications for education are to view giftedness

from a developmental perspective, to be aware of the great variety within this group and to

aim for tailor made solutions.


References

Abdel-Khalek, A. M. (2005). Reliability and factorial validity of the standard progressive

matrices among Kuwaiti children ages 8 to 15 years. Perceptual and Motor Skills,

101, 409-412. doi:10.2466/pms.101.2.409-412

Al-Issa, I (1964). Creativity and its relationship to age, vocabulary and personality of

schizophrenics. The British Journal of Psychiatry, 110(464), 74-79

Barbot, B., M., & Lubart, T. I. (2011). Assessing creativity in the classroom. The Open

Education Journal, 4, 58-66. doi: 10.2174/1874920801104010058

Baum, S. M., & Olenchak, F. R. (2002). The alphabet children: GT, AHDH, and more.

Exceptionality, 10, 77-91.

Beaty, R. E., Nusbaum, E. C., & Silvia, P. J. (2014). Does insight problem solving predict

real-world creativity? Psychology of Aesthetics, Creativity, and the Arts.

doi: 10.1037/a0035727.

Benedek, M., Franz, F., Heene, M., & Neubauer, A. C. (2012). Differential effects of

cognitive inhibition and intelligence on creativity. Personality and Individual

Differences, 53, 480-485. doi: 10.1016/j.paid.2012.04.014

Benedek, M., Jauk, E., Sommer, M., Arendasy, M., Neubauer, A. C. (2014). Intelligence,

creativity, and cognitive control: The common and differential involvement of

executive functions in intelligence and creativity. Intelligence, 46, 73–83.

doi: 10.1016/j.intell.2014.05.007

Broos, A., Fulker, D. W., & De Fries, J. C. (1990). Reading performance and general

cognitive ability: A multivariate genetic analysis of twin data. Personality and

Individual Differences, 11, 141-146. doi: 10.1016/0191-886

Bruner, J. S. (1985). The role of interaction formats in language acquisition. In J. P. Forgas

(Ed.), Language and social situations, 31-46. New York: Springer Verlag.

Carson, S. H., Peterson, J. B., & Higgins, D. M. (2003). Decreased latent inhibition is

associated with increased creative achievement in high functioning individuals.

Journal of Personality and Social Psychology, 85, 499-506.

Cattell, R. B. (1963). Theory of fluid and crystallized intelligence: A critical experiment.

Journal of Educational Psychology, 54(1), 1-22. doi: 10.1037/h0046743

Chakravarty, A. (2009). Artistic talent in dyslexia: A hypothesis. Medical Hypotheses, 73,

569–571. doi: 10.1016/j.mehy.2009.05.034.

Chermahini, S. A., & Hommel, B. (2010). The (b)link between creativity and dopamine:

Spontaneous eye blink rates predict and dissociate divergent and convergent thinking.

http://dx.doi.org/10.1016/j.paid.2012.04.014


Cognition, 115/3, 458-465. doi.org/10.1016/j.cognition.2010.03.007

Chu, T-L., & Lin, W-W. (2013). Uniqueness, integration or separation? Exploring the nature

of creativity through creative writing by elementary school students in Taiwan.

Educational Psychology: An International Journal of Experimental Educational

Psychology, 33:5, 582-595, doi: 10.1080/01443410.2013.821459

Clarke, P. J., Snowling, M. J., Truelove, E., & Hulme, C. (2010). Ameliorating children’s

children’s reading comprehension difficulties: A randomized controlled trial.

Psychological Science, 21, 1106-1116. doi. 10.1177/0956797610375449

Cornwall, A. (1992). The relationship of phonological awareness, rapid naming and verbal

memory to severe reading and spelling disability. Journal of Learning Disabilities, 25,

532-538.

Cramond, B. (1994). Attention deficit hyperactivity disorder and creativity—What is the

connection? Journal of Creative Behavior, 28, 193-210.

Cropley, A. (2006). In praise of convergent thinking. Creativity Research Journal, 18(3),

391-404. doi. 10.1207/s15326934crj1803_13

Eide, B. L., & Eide, F. F. (2011). The dyslexic advantage: Unlocking the hidden potential of

the dyslexic brain. London, UK: Hay House.

Engle, R. W. (2002). Working memory capacity as executive attention. Current Directions in

Psychological Science, 11, 19–23.

Finch, M. E. H., Neumeister, K. L. S., Burney, V. H., & Cook, A. L. (2014). The Relationship

of Cognitive and Executive Functioning With Achievement in Gifted Kindergarten

Children. Gifted Child Quarterly, 58, 167–182. doi: 10.1177/0016986214534889

Haensly, P. A., and Torrance, E. P. (1990). Assessment of creativity in children and

adolescents. In Reynoolds, C. R. and Kamphaus, R. W. (eds) Handbook of

Psychological and Educational Assessment of Children: Intelligence and

Achievement. New York: Gildford.

Hansenne, M., & Legrand, J. (2012). Creativity, emotional intelligence and school

performance. International Journal of Educational Research, 53, 264-268.

doi: 10.1016/j.ijer.2012.03.015

Jauk, E., Benedek, M., Dunst, B., & Neubauer, A. C. (2013). The relationship between

intelligence and creativity: New support for the threshold hypothesis by means of

empirical breakpoint detection. Intelligence, 41. doi:10.1016/j.intell.2013.03.003.

Jung, R. E., Gaspararovic, C., Chaves, R. S., Flores, R. A., Smith, S. M., Caprihan, A., &

Yeo, R. A. (2009). Biochemical support for the “threshold” theory of creativity: a

http://dx.doi.org/10.1016/j.ijer.2012.03.015


magnetic resonance spectroscopy study. The Journal of Neuroscience, 29, 5319-

5325. doi: 10.1523/JNEUROSCI.0588-09.2009

Karwowski, M., & Gralewski, J. (2013). Threshold hypothesis: fact or artefact? Thinking

Skills and Creativity, 8, 25-33. doi:10.1016/j.intell.2013.03.003

Kiefer, M., & Martens, U. (2010). Attentional sensitization of unconscious cognition: Task

sets modulate subsequent masked semantic priming. Journal of Experimental

Psychology: General, 139, 464-489. doi.10.2478%2Fv10053-008-0102-4

Kim, K. H. (2005). Can only intelligent people be creative? Journal of Secondary Gifted

Education, 16, 57-66. doi: 10.4219/jsge-2005-473

Kroesbergen, Van Hooijdonk, Middel-Lalleman, Rijnders, & van Viersen (2015). The

psychological well-being of early identified gifted children.

Liegeois, F., Cross, J. H., Polkey, C., Harkness, W., & Vargha-Khadem, F. (2008) Language

after hemispherectomy in childhood: contributions from memory and intelligence.

Neuropsychologia, 46, 3101-3107. doi: 10.1016/j.neuropsychologia.2008.07.001

Lubow, R. E., Gewirtz, J. C. (1995). Latent inhibition in humans: data, theory, and

implications for schizophrenia. Psychological Bulletin, 117 (1): 87–103.

doi:10.1037/0033-2909.117.1.87

Mann, E. L. (2006). Creativity: The essence of mathematics. Journal for the Education of

the Gifted, 30, 236-260. doi:10.4219/jeg-2006-264.

Oakhill, J., & Cain, K. (2007). Issues of causality in children’s reading comprehension. In D.

S. McNamara (Eds.), Reading comprehension strategies. Theories, interventions and

technologies (47-71). Mahwah, N. J.: Lawrence Erlbaum Associates Inc.

Perfetti, C. A. (1985). Reading ability. New York: Oxford University Press.

Preckel, F., Götz, T., & Frenzel, A. (2010). Ability grouping of gifted students: effects on

academic self-concept and boredom. British Journal of Educational Psychology, 80,

451-472. doi: 10.1348/000709909X480716

Popov, A. (1992). Creativity and reading comprehension. The Journal of Creative Behavior,

26(3), 206-212Raven, J. (2000). The Raven’s Progressive Matrices: change and

stability over culture and time. Cognitive Psychology, 41, 375-386.

doi:10.1006/cogp.1999.0735.

Posner, M. I., & Snyder, C. R. R. (1975). Attention and cognitive control. In R. L. Solso

(Ed.), Information processing and cognition: The Loyola symposium (pp. 55-85).

Hillsdale: Lawrence Erlbaum Associates.

Renzulli, J. S. (1986). The three-ring conception of giftedness: a developmental model for

http://dx.doi.org/10.1016/j.neuropsychologia.2008.07.001

http://en.wikipedia.org/wiki/Digital_object_identifier

http://dx.doi.org/10.1037%2F0033-2909.117.1.87


creative productivity. In R. Sternberg & J. Davidson (Eds.), Conceptions of giftedness

(pp. 332-357). New York: Cambridge University Press.

Ritchie, S. J., Luciano, M., Hansell, N. K., Wright, M. J., Bates, T. C. (2013). The

relationship of reading ability to creativity: positive, not negative associations.

Learning and Individual Differences, 26, 171–176. doi: 10.1016/j.lindif.2013.02.009

Runco, M. A., & Acar, S. (2012). Divergent thinking as an indicator of creative potential.

Creativity Research Journal, 24, 66-75. doi:10.1080/10400419.2012.652929

Runco, M. M., & Albert, R. S. (1986). The threshold theory regarding creativity and

intelligence: an empirical test with gifted and nongifted children. Creative Child and

Adult Quarterly J 1(4), 212-218. doi: 1988-07120-001

Runco, M. A. (2004). Creativity. Annual Review of Psychology, 55, 657-687. doi:

10.2466/pms.1984.59.3.711

Samuels, S. J., & Flor, R. F. (1997). The importance of automaticity for developing expertise

in reading. Reading and Writing Quarterly: Overcoming Reading Difficulties, 13,

107–121.

Schneider, W., & Shiffrin, R. M. (1977). Controlled and automatic human information

processing: I. Detection, search, and attention. Psychological Review, 84, 1-66.

Stanovich, K. E. (1986). Matthew effects in reading: some consequences of individual

differences in the acquisition of literacy. Reading Research Quarterly, 21, 360-407.

doi. 10.1598/RRQ.21.4.1

Stanovich, K. E., Cunningham, A., & Freeman, D. (1984). The relationship between early

reading acquisition and word decoding with and without context: A longitudinal study

of first-grade children. Journal of Educational Psychology, 76, 668-677.

doi:10.1037/022-0663.76.4.668

Strang, R. (1968). Reading diagnosis and remediation (ERIC CRIER Reading Review Series).

Newark, DE: International Reading Association.

Subotnik, R. F., Olszewski-Kubilius, P., & Worrell F. C. (2011). Rethinking giftedness and

gifted education: a proposed direction forward based on psychological science.

Psychological Science in the Public Interest, 12, 3– 54.

doi: 10.1177/1529100611418056

Subotnik, R. F., & Rickoff, R. (2010). Should eminence based on outstanding innovation be

the goal of gifted education and talent development? Implications for policy and

research. Learning and Individual Differences, 20, 358–364.

doi: 10.1016/j.lindif.2009.12.005

http://dx.doi.org/10.1016/j.lindif.2013.02.009


Tafti, M. A., Hameedy, M. A., & Baghal, N. M. (2009). Dyslexia, a deficit or a difference:

Comparing the creativity and memory skills of dyslexic and nondyslexic students in

Iran. Social Behavior and Personality: An International Journal, 37, 1009–1016.

doi: 10.2224/sbp.2009.37.8.1009

Tien, Y.-M., Hsu, L.-C., Tai, J. H.-Y, Yang, Y.-F. (2014). Deciphering syntactic processing of

gifted students with working memory and creativity. Chinese Journal of Psychology.

56(3), 257-276

Torrance, E. P., Ball, O. E., & Safter, T. H. (2008). Torrance® Test of Creative Thinking.

Streamlined Scoring Guide for Figural Forms A and B. Illinois: Scholastic Testing

Service, Inc.

Unsworth, N., & Engle, R. W. (2007). The nature of individual differences in working

memory capacity: Active maintenance in primary memory and controlled search from

secondary memory. Psychological Review, 114, 104–132. doi: 10.1037/0033-

295X.114.1.104

Vartanian, O. (2009). Variable attention facilitates creative problem solving. Psychology of

Aesthetics, Creativity, and the Arts, 3, 57–59. doi: 10.1037/a0014781

Whitmore, J. R. (1980). Giftedness, conflict, and underachievement. Boston: Allyn and

Bacon.

Wolf, K. M. & Mieg, H. A. (2010). Cognitive determinants of the success of inventors:

complex problem solving and deliberate use of divergent and convergent thinking,

European Journal of Cognitive Psychology, 22(3), 443-462,

doi: 10.1080/09541440902916845

Yamatoto, K. (1964a). Threshold of intelligence in academic achievement of highly creative

students. The Journal of Experimental Education, 32, 401–405.

Yamamoto, K. (1964b). The Experimental Scoring Manual for Minnesota Tests for Creative

Thinking and Writing. Kent State University. Bureau of Educational Research.

Zabelina, D. L., & Robinson, M. D. (2010). Creativity as flexible cognitive control.

Psychology of Aesthetics, Creativity, and the Arts, 4, 136–143. doi: 10.1037/a0017379

http://dx.doi.org/10.2224/sbp.2009.37.8.1009

Masterthesis E. Bekker-Janssens [4254694]

Documents

Transcript of Masterthesis E. Bekker-Janssens [4254694]