International Journal of Intelligence Science, 2011, 1, 17-24
doi:10.4236/ijis.2011.12003 Published Online October 2011 (
Copyright © 2011 SciRes. IJIS
Dissociating Improvement of Attention and Intelligence
during Written Language Acquisition in Adults
Steffen Landgraf1,2,3, Reinhard Beyer1, Ann Pannekamp1, Gesa Schaadt1, Darina Koch1,
Manja Foth1, Elke van der Meer1,2
1Humboldt-Un iversität zu Berlin, Institute of Psychology, Berlin, Germany
2School of Mind and Brain, Berli n, Germany
3Sorbonne University, Paris, France
Received July 28, 2011; revised September 22, 2011; accepted September 30, 2011
About one tenth of the world’s population cannot read and write sufficiently. Cognitive abilities, such as se-
lective attention and crystallized as well as fluid intelligence, have been defined as crucial factors for the ac-
quisition of written language skills. However, it is unclear whether these abilities are necessary also for the
alphabetization of adults. Before and after a one-year alphabetization course, we compared the attention and
intelligence of 47 illiterate individuals to 41 matched literate controls who did not take part in the alphabeti-
zation course. Illiterate individuals improved in selective attention and crystallized intelligence from before
to after the alphabetization course; however, they did not reach the same level of functioning as literate con-
trols. In addition, the fluid intelligence of illiterates did not improve. More importantly, when controlling for
attention improvement, we found that improvement in crystallized intelligence was associated with alpha-
betization above and beyond the influence of attention. Our results suggest that alphabetization is closely
related to improvements in attention and crystallized intelligence. Specifically, socio-cultural, knowledge-
specific learning processes improve during the acquisition of written language skills and may not depend on
only the enhancement of the ability to attend to relevant stimuli. Alphabetization programs may, therefore,
benefit from distinct considerations of attentional, intellectual, and literacy related skill acquisitions.
Keywords: Alphabetization Course, Illiterate Adults, Crystallized Intelligence, Fluid Intelligence, Attention,
Written Language Acquisition
1. Introduction
This One challenge of modern societies is to educate
their members in reading and writing, the so called al-
phabetization. Worldwide, there are about 796 million
illiterate individuals, two thirds of whom are women [1].
Even in highly developed countries such as Germany,
7.5 million individuals cannot read or write proficiently
[2]. Hence, understanding and improving the effective-
ness of alphabetization programs is of great interest.
Whereas there have been multiple investigations of cog-
nitive abilities and their association with literacy, rather
little is known about the cognitive processes underlying
actual alphabetization. The present study investigates
precisely this issue, looking at specific cognitive abilities
and their contribution to alphabetization in illiterate
Cognitive abilities, such as phonological awareness,
attention, and intelligence, have been proposed to be
associated with written language acquisition (for a dis-
cussion on phonological awareness, please refer to [3]).
Baddeley’s working memory model [4,5] assigns a pri-
mordial role to a “central executive” regarding the ability
to attend to relevant and to inhibit irrelevant information.
Attention and intelligence may be crucial for written
language acquisition because they are of utmost impor-
tance during learning [6-9]. In fact, intelligence and at-
tention relate to alphabetization as they allow effective
investment of cognitive resources during educational
processes [10,11].
Regarding literacy, a plethora of studies has shown
that it is robustly associated with central executive func-
tioning. For example, verbal span of preschoolers can
predict future written language skills [12]. Further,
working memory span in fourth to sixth graders is asso-
ciated with the ability to read, specifically with faster
reading speed [13]. Interestingly, the interrelation be-
tween central executive and written language skills (e.g.,
decoding speed) increases with increasing reading abili-
ties: good readers show stronger associations than poor
readers, indicating that a lack of exposure to written lan-
guage leads to a weak automatization of relevant cogni-
tive processes [14,15]. Consequently, for individuals
with weakly developed reading and writing skills, under-
standing written language requires a greater investment
of cognitive abilities, which results, in turn, in impaired
Individuals with poor central executive abilities show
also less flexible selective attention [16]. Reference [17]
points out that decreased selective attention reduces al-
phabetization success, supporting the assumption that
attention plays a decisive role in written language acqui-
sition. Yet its interrelation with other cognitive abilities
during written language acquisition in adults is rather
unknown. With the present study, we investigated whe-
ther the influence of alphabetization on selective atten-
tion could be dissociated from the influence on other
cognitive abilities associated with the central executive,
namely, intelligence.
Intelligence is strongly associated with the allocation
of cognitive resources [18] and may facilitate the acqui-
sition and maintenance of written language skills. Ac-
cording to the general intelligence model of Cattel [19],
there are two intelligence factors: fluid and crystallized.
Fluid intelligence describes the capacity to find solutions
for complex problems in new situations—a decisive fac-
tor for learning processes [8,20-22]. According to the
investment theory [23], problem solving, reasoning, or
classifying allow an efficient adaptation to new situations
in which stable representations of new knowledge are
formed [24]. Knowledge acquisition correlates positively
with fluid intelligence level [6-9], especially if the learn-
ing process is highly complex and innovative [8,20,21,
25]. During alphabetization the learner is confronted
with new and complex situations, implying a complex
learning pattern [26]. For example, rhyme detection [27,
28] and syllable discrimination [29,30] have already
been developed before entering primary school. These
abilities are relevant not only for structuring written lan-
guage, but they are important also for substituting pre-
fixes and suffixes in order to change word meanings [31].
Fluid intelligence may support these processes and, con-
sequently, it may support the acquisition of written lan-
guage. Nevertheless, socio-cultural factors contributing
to the manifestation of content-specific knowledge may
affect alphabetization even more specifically.
Crystallized intelligence accounts for the capacity to
accumulate knowledge based on socio-cultural and edu-
cational background [19,23,32]. It is influenced, though
not exclusively, by fluid intelligence and environment-
specific learning conditions such as, for example, paren-
tal socio-economic status [33]. Crystallized knowledge
can be applied to solve content-specific problems [34,
35]. For example, while non-alphabetic, idiosyncratic
symbols, such as Arabic numbers, do not represent pho-
netic or graphemic units, they reflect pronounceable
words [36]. Illiterates are able to acquire the Arabic
number system informally [37] and can even conduct
various, though simple, calculations [10,38,39]. The pro-
ficiency in manipulating numbers indicates that symbol
systems associated with simple written language de-
mands can be acquired by illiterates, even without formal
education. This form of learning, which is strongly de-
pendent on crystallized intelligence, influences also the
alphabetization process.
In the present study, the main question was whether
the influence of alphabetization on attention and intelli-
gence could be dissociated. We assessed selective atten-
tion as well as fluid and crystallized intelligence of illit-
erate adults before and after a one-year alphabetization
course. We hypothesized that specifically crystallized
intelligence scores would improve during the alphabeti-
zation course. Further, in order to dissociate attention
and intelligence improvement during written language
acquisition, we subdivided illiterates into two groups:
those who improved significantly in selective attention
during the alphabetization course and those who did not.
We expected improvements in attention to affect im-
provements in intelligence if attentional abilities were the
driving factors of alphabetization. Finally, we compared
attention and intelligence between illiterate and literate
2. Material and Methods
2.1. Partic ipa n ts
Literate controls (n = 41) were matched to illiterate indi-
viduals (n = 47; Table 1). All illiterate individuals and
three literate controls were of non-German origin who
have been living in Germany for an average of 11.5 years
(standard deviation, SD = 7.8 y) at the time of testing.
Literate controls were carefully selected regarding edu-
cation duration. The study followed guidelines in accor-
dance with the Declaration of Helsinki (1964). All par-
ticipants were paid and provided consent before inclu-
Copyright © 2011 SciRes. IJIS
Table 1. Demographic information for the two participant
Illiterate group Literate group
N 47 41
Gender 29F 21F
Age 38.3 (8.8) 34.0 (11.3)
Years of education 4.4 (3.9) 11.2 (1.4)
Handedness 44R, 3L 39R, 1L, 1M
Course attendance (days) 132 (34) -
Note: N = number of participants; F = females; years of education = number
of years individuals spent in regular school (12 = university entrance certi-
fication); R = right-handed; L = left-handed; M = mixed-handed; course
attendance = length of time illiterates took part in the alphabetization course;
numbers in parentheses = standard deviations.
2.2. Materials
2.2.1. Procedure
To evaluate the improvement of abilities associated with
alphabetization, the illiterate group was tested before
being included in the course (T1) and after having been
trained (one year later, T2). The alphabetization course
entailed weekly sessions where participants were pre-
sented with letters, words, and short phrases from dif-
ferent topics relevant to their daily lives (e.g., buying
groceries). In addition to visual and auditory material for
each new letter, participants received feedback each
week about their performance. With increasing compe-
tence level, participants were offered the possibility to
self-paced e-learning.
There was only one testing session for the literate con-
trols since they did not participate in the alphabetization
course. Participants were tested in groups of ten. The
order of tests was always in the order in which they are
described below. Due to technical difficulties, the data
from the d2 test for two illiterate individuals and the data
from the CFT-20-R for one illiterate individual were
excluded from analyses.
2.2.2. Stimuli
The d2 test of attention. The d2 test [40] is a language-
independent test that evaluates selective attention. The
test requires participants to detect and cross out targets
(letter d with two dashes) as quickly and accurately as
possible while ignoring distracters (e.g., letter d with one
or three dashes). The test consists of 14 rows, each con-
taining 47 signs. The time limit for each row is 20 s. We
report a measure for attention calculated from the quality,
quantity, and time of the d2 performance. The test takes
8 minutes.
CFT-20-R. The CFT-20-R is a language-free test as-
sessing fluid intelligence [19] independently of culturally
specific knowledge [41]. The first part of the CFT-20-R
consists of four subtests, namely, sequence completion,
classification, matrices, and topology. The tasks of each
subtest are in multiple-choice formats and are ordered
from easiest to most difficult. The number of correct
responses allows for the calculation of a fluid intelli-
gence score. The test takes 14 minutes.
CFT-ZF-R. The CFT-ZF-R is also a language-free test
assessing crystallized intelligence [19] by testing nu-
merical processing capacity [41]. It consists of 21 multi-
ple-choice tasks in which number sequences have to be
continued in a logical way. The number of correct re-
sponses allows for the calculation of a crystallized intel-
ligence score. The test takes 12 minutes.
2.2.3. Data Analysis
PASW 18 (Predictive Analysis SoftWare) was used to
perform statistical analyses. Data were, unless otherwise
specified, normally distributed (Kolgomorov-Smirnov
test). The significance level for all statistical tests was
For all tests, the raw data were converted into stan-
dardized values representing percentile ranks. A percen-
tile rank of 25%, for example, implies that the individual
performed better than 25% and worse than 75% of his/
her age group.
To investigate whether the illiterate group improved
on the experimental measures, we used paired t-tests
with time of testing (before the alphabetization or T1 vs.
after the alphabetization course or T2) as a within-sub-
jects factor for the illiterate group. Further, the test re-
sults were compared between groups (illiterate vs. liter-
ate) using independent t-tests separately for the first (T1)
and the second (T2) testing sessions of the illiterate
To dissociate the influence of attention and intelli-
gence on written language acquisition, we subdivided the
illiterate group based on their improvement on the d2 test:
high d2 improvement and low d2 improvement from T1
to T2. We investigated whether both subgroups different-
tially improved on the other tests. In other words, did
individuals who improved highly (weakly) on the d2 also
improve highly (weakly) on the other tests? There were
two approaches to test this. First, we compared test per-
formances between times of testing (T1 vs. T2) using
paired t-tests individually for the two subgroups. Second,
we calculated an improvement measure for each test as
the difference between test performance at T2 minus test
performance at T1. We then used independent sample
t-tests to compare improvements between subgroups
(illiterates who showed low vs. high d2 improvement) in
each test.
Copyright © 2011 SciRes. IJIS
3. Results
3.1. Demographic Variables
The literate and illiterate groups did not differ in gender,
= 0.98, p > 0.05), age (t(86) = 2.03, p > 0.05, or
=1.90, p > 0.05, but did differ in years
of education, t(59) = 11.12, p < 0.01; see Table 1.
3.2. d2 Test of Attention
Participants in the illiterate group improved in d2 per-
formance from T1 to T2, t(44) = 5.71, p < 0.01. Com-
pared to the literate group, participants in the illiterate
group performed worse at T1, t(57.35) = 8.62, p < 0.01,
and at T2, t(83) = 3.98, p < 0.01; see Table 2.
3.3. CFT-20-R
Participants in the illiterate group did not improve in
their fluid intelligence scores from T1 to T2, t(45) =
1.79, p > 0.05. Illiterate individuals showed worse per-
formance at T1, t(66.99) = 11.31, p < 0.01, and T2, t(85)
= 9.67, p < 0.02, compared to the literate group.
3.4. CFT-ZF-R
Participants in the illiterate group improved in their
crystallized intelligence scores from T1 to T2, t(46) =
2.69, p < 0.01. Compared to the literate group, the illit-
erate group’s performance was worse at T1, t(43.99) =
9.37, p < 0.01, and T2, t(67.35) = 7.11, p < 0.01.
3.5. Controlling for Attention
According to the d2 improvement of the illiterate group,
we differentiated between a high-improvement subgroup
(HI, mean d2 improvement = 41.9 (±18.6) percentile
ranks, n = 17) and a low-improvement subgroup (LI,
Table 2. Results of the cognitive tests for the illiterate group
(two assessment s) and the literate group (one assessment).
Illit erate gr ou p
Before the
After the
Literate group
d2 7.2 (15) 25.0 (30) 49.9 (28)
CFT-20-R 7.4 (18) 11.1 (24) 63.6 (27)
CFT-ZF-R 2.0 (7) 8.0 (20) 47.4 (30)
Note: All values are given in percentile rank according to the tests’ manuals.
On all tasks and at all times, the illiterate group performed worse than the
literate group. Numbers in bold for the illiterate group indicate improve-
ments in percentile rank from before to after the alphabetization class.
mean d2 improvement = 0.8 (±1.2) percentile ranks, n =
15). This enabled us to control for the influence of atten-
tion improvement regarding the improvement of intelli-
gence during written language acquisition without rely-
ing on, e.g., correlational analyses. Regarding the CFT-
20-R (fluid intelligence), neither subgroup improved
from T1 to T2 (HI-group: t(14) = 1.58, p > 0.05;
LI-group: t(15) = 1.51, p > 0.05). Further, the CFT-20-R
improvement score (score at T2 minus score at T1) did
not differ between subgroups, t(29) = 1.45, p > 0.05.
Regarding the CFT-ZF-R (crystallized intelligence), the
subgroup improving strongly in d2 scores showed a trend
toward improvement from T1 to T2 (HI-group: t(14) =
1.83, p = 0.09; LI-group: t(15) = 1.45, p > 0.05). The
subgroups did not differ in CFT-ZF-R improvement, t(29)
= 1.80, p > 0.05. Together, these results suggest that
selective attention improvement during the alphabetiza-
tion course is mostly unrelated to the improvement in
intelligence during the same period (see Figure 1).
4. Discussion
The present study investigated how attention and intelli-
gence are affected by alphabetization in illiterate adults.
Whereas crystallized intelligence and selective attention
improved from before to after the alphabetization course,
fluid intelligence did not. When controlling for attention
improvements, the improvement patterns of intelligence
during the alphabetization course did not change: crys-
tallized intelligence improved regardless of attention;
fluid intelligence did not improve regardless of attention.
Despite showing enhanced selective attention and crys-
tallized intelligence at the end of the alphabetization
course, illiterate individuals did not reach the perform-
ance levels of literate individuals. We conclude that im-
provements of selective attention during alphabetization
do not necessarily influence intelligence improvements.
Thus, attention and intelligence measures may make
unique contributions to the acquisition of written lan-
guage skills.
According to our main hypotheses, during alphabeti-
zation adult illiterates selectively improve in their cogni-
tive abilities. Attention and crystallized intelligence im-
provements paralleled the administration of a one-year
alphabetization course. This is in line with studies show-
ing that better attention and intelligence scores are asso-
ciated with higher alphabetization [17,31,37]. Further-
more, crystallized intelligence can be improved as a
function of available knowledge and intellectual de-
mands [42-44]. Due to developing literacy, there is an
acquisition of new knowledge, which can be applied to
new situations. As a consequence, previously inaccessi-
ble information can be accessed and, in turn, serves as a
Copyright © 2011 SciRes. IJIS
Copyright © 2011 SciRes. IJIS
D2 Hi gh Im pr ovement
Percentile Rank
D2 Low Impr ovem ent
Percentile Rank
Figure 1. (a) Intelligence test perfor mance (CFT-20-R and CFT-ZF-R) of the d2 high-improving group (HI) at T1 (before the
alphabetization course) and T2 (after the alphabetization course); (b) Intelligence test performance (CFT-20-R and
CFT-ZF-R) of the d2 low-improving group (LI) at T1 (before the alphabetization course) and T2 (after the alphabetization
course). Note: in the D2 high-improving group, variability of the percentile rank was more pronounced compared to the D2
low -improvi ng g ro up. Thi s may hav e be en du e t o the f act th at the maj ori t y of i ndi vidual s i n t h e D 2 l ow - i mprovi ng g rou p ha d
zero improvement; in other words a floor eff ect.
foundation for providing new knowledge input and new
knowledge manifestation.
More importantly, our results showed that the process
of “crystallizing” new knowledge appears to be possible
even above and beyond the influence of attentional func-
tions. We dissociated the improvement of crystallized
intelligence and selective attention. Specifically, we con-
trolled for attention by subdividing illiterate individuals
according to their attentional improvement score. This
method has, to our knowledge, not been used before. By
explicitly not relying on correlational analyses, which are
typically used in the literature, we demonstrate that crys-
tallized intelligence increased regardless of whether at-
tention improved or not. This specifies former research
showing that automatization of cognitive processes in-
creases with better written language abilities [14,15].
Specifically, exposure to written language requires illit-
erates to allocate more cognitive resources and, therefore,
to extensively practice intellectual abilities during al-
phabetization programs. According to our results, this
allocation of cognitive resources may be independent of
attention training effects.
Fluid intelligence measures did not improve and were
also not influenced by attention improvement during
alphabetization. According to Cattell [19], fluid intelli-
gence is a decisive factor when learning to solve [8,21,
22] and when actually solving complex problems [20,
25]. The results of the present study suggest that alpha-
betization does not reflect improvements in fluid intelli-
gence. This may be due to the fact that in order to ac-
quire written language skills, children rely on cognitive
abilities that were acquired before entering primary
school [26-29] and that may be culturally specific [45].
For example, [46,47] showed that children from the
United Kingdom and from Zambia did not differ when
reproducing abstract patterns with clay. However, British
outperformed Zambian children when reproducing pat-
terns with papers and pencils. By contrast, Zambian were
better than British children when reproducing patterns
with wires. Hence, the familiarity with material proper-
ties can influence the development of cognitive abilities
[48], implying that the ability to recognize rules or regu-
larities and to draw inferences [49] can be supported by
domain-specific learning processes and knowledge [33].
Instead of fluid intelligence, culture-specific expertise,
that is, crystallized intelligence, may be the decisive fac-
tor for written language acquisition success [50].
In line with former studies [51,52], our results confirm
that illiterate individuals do not reach cognitive abilities
as shown by literate controls. Indeed, in cognitive tests
that are related to written language, illiterate individuals
have demonstrated performance comparable to that of
preschoolers [51]. In the present study, it can be assumed
that the cognitive abilities of illiterate individuals were
not trained as effectively as would have been necessary
in order to reach the level of literate individuals. Before
the alphabetization course, attention was below the lower
norm. The decreased exposure to educationally relevant
contents mediated by illiteracy may have impeded the
development of cognitive functions [10,53-56]. Thus, the
weak automatization of cognitive processes affects the
effective interplay regarding not only written language
skills, but also attention and intelligence. During adult-
hood, this may increase difficulties when acquiring new
knowledge, specifically written language skills.
The present investigation has some limitations. The
sample size was small and the duration of the alphabeti-
zation course was relatively short. Future studies should
look further into, first, how cognitive abilities can be
improved. Second, given the difference in fluid intelli-
gence between the literate and illiterate group in our
sample, future investigations should investigate how il-
literate individuals can possibly reach the level of literate
individuals longitudinally. Third, the control group was
only tested once whereas the illiteracy group was tested
twice. Spontaneous learning might have taken place in
the illiteracy group due to repeated test exposure. How-
ever, there were more than 12 months between the two
testing sessions making it unlikely to produce improve-
ment effects. Moreover, there is no evidence for per-
formance improvement due to multiple testing in the
d2-test [40]. Fourth, as a function of illiterates catching
up with literates, individual written language acquisition
learning rates could be identified in order to characterize
the postulated increase of automatization and interrela-
tion between cognitive abilities. Consequently, the pre-
dictive power of cognitive abilities, their interrelations,
and individual improvements could be strengthened as a
prerequisite for the optimization of alphabetization pro-
5. Conclusions
This study illuminated specific aspects of the interplay
between attention, intelligence, and alphabetization. Se-
lective attention and crystallized intelligence, but not
fluid intelligence, of illiterate adults improved during a
one-year alphabetization course. However, illiterates did
not attain the same level of cognitive functioning as
shown by literate controls. Interestingly, crystallized
intelligence improved above and beyond the influence of
attentional improvement. These results suggest, first, that
alphabetization is closely related to improvements in
attention and socio-cultural (i.e., knowledge-specific)
learning processes. Second, these learning processes
probably do not depend on only an increase in the ability
to attend to relevant stimuli. Third, alphabetization suc-
cess may be improved by taking into account attention,
intelligence, and literacy related factors, separately.
6. Acknowledgements
This research was supported by a grant from the German
Federal Ministry for Education and Research (01AB
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