Masterthesis E. Bekker-Janssens [4254694]

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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

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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.

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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.

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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

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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

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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.

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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,

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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

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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

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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

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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).

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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

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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).

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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

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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

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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

17
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.

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