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DOI: https://doi.org/10.34069/AI/2024.73.01.12
How to Cite:
Spasova, L. (2024). Gender and education as factors for determining the verbal-visual affiliation of individuals. Amazonia
Investiga, 13(73), 155-164. https://doi.org/10.34069/AI/2024.73.01.12
Gender and education as factors for determining the verbal-visual
affiliation of individuals
Пол и образование като фактори за определяне на вербално-визуалната принадлежност на
индивидите
Received: December 1, 2023 Accepted: January 15, 2024
Written by:
Lyubomira Spasova1
https://orcid.org/0000-0002-1438-9104
Abstract
Gender and education are two of the socio-
demographic characteristics that are studied to
establish individual differences in personality.
The purpose of the present research is to
determine the susceptibility of individuals to the
VVQ, adapted and modified from Kirby et al.,
and to show the influence of gender and
education in the segmentation of verbalizers,
visualizers, and dreamers. In the study, a valid
and reliable instrument for measuring
susceptibility to VVQ, prepared in advance by
the author, was applied. The results of the
analysis of variance (ANOVA) have showed a
strong susceptibility of respondents to the
Verbalizer Scale of women, as well as
susceptibility to the Dreamer Scale of men.
When considering the influence of education on
VVQ, it was found that respondents with a
master's degree were highly visual, and
respondents with a doctoral degree were highly
verbal. On Dreamer Scale, susceptibility was
greatest again among respondents with a doctoral
degree. The results of the analysis of covariance
(ANCOVA) indicated that male advertising
consumers with a master's degree were more
receptive to the Verbalizer Scale, as were female
respondents with a doctoral degree relative to all
other target groups. These scientific results can
be useful for advertisers, marketers, as well as
specialists in cognitive psychology.
Keywords: verbal-visual cognitive styles,
advertising segmentation, VVQ.
1
PhD in Social Communications and Information Sciences, Senior Lecturer, Trakia University, Faculty of Economics, Department
of Social Sciences and Business Language Training, Strara Zagora, Bulgaria. WoS Researcher ID: GYJ-1692-2022
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Introduction
The verbal and visual components of advertising
are a highly beneficial topic for exploration
among researchers investigating cognitive styles
– verbalizers versus visualizers, and some even
as dreamers in information processing. In each
advertisement, various visual and verbal effects
are employed to influence consumers, and
research is progressing in various directions.
Researchers express different opinions on this
matter in various fields (Wanta & Roark, 1994;
Zillmann et al., 1999; Mendelson, 2001;
Mendelson & Thorson, 2003). One perspective is
that the intriguing aspects of visual information
involve processing cognitive elements in
advertising as a significant part of the consumer
experience, evoking pleasant or unpleasant
feelings (Lagerwerf et al., 2012, p. 1837).
Furthermore, each metaphor in advertising can
be interpreted differently by consumers with
various characteristics. There is evidence that
individual differences in personality and
cognitive style affiliation influence how
variables impact the ultimate responses of
consumers. Despite these indications of effective
influence, the researcher believes that the
achieved effects on consumers belonging to
different segments of the advertising audience
are not sufficiently explored. This is the reason to
explore new segments of users, divided into
visualizers, verbalizers and dreamers, where
other demographic characteristics are taken into
account, as well as factors of achieved verbal-
visual influence. In a number of scientific
studies, the achieved effects of verbal-visual
impact are discussed, but they have not
sufficiently studied how the intangible benefits
derive from the material aspects of the product or
service offering (Phillips, 2000). In addition, it
should be established in more detail which
segments of consumers belonging to different
genders and with different educational
characteristics react more quickly to verbal-
visual impact through advertising. In support of
this statement are studies conducted in the late
1990s of the 20th century (Adaval & Wyer,
1998) and the beginning of the 21st century
(Mattila, 1999), in which it was found that the use
of narratives through pictures as a specific a type
of visualization strategy, leads to more favorable
evaluations of the various advertising media
presented in the media. However, there is a need
for new scientific evidence regarding the
achievement of advertising effectiveness through
verbalization and visualization as both user
experience and user segmentation.
Literature review
The information processing process is complex
and finds its empirical support, on the one hand,
in the theory of limited capacity, in which a
distinction is made between different channels of
processing - visual and verbal (Lang et al., 2000;
Lang et al., 2002), as well as in dual coding
theory, where optimal coding of textual and
visual information is observed (Paivio, 1986). In
addition, research in the field of cognitive
psychology shows that there are two types of
information processing - verbal and visual or
combined, because these are the two main
components that make up any information
system. Researchers have presented in their
scientific works a number of different cognitive
styles that can influence information processing
and also directly relate to the perception of
verbal-visual components in information
processing (Witkin et al., 1977), in holistic and
analytic processing, (Riding & Sadler-Smith,
1992), or reflective and impulsive processing
(Holman, Snowman, & Deichmann, 1979). In
media studies, scholars are interested in both
cognitive styles and "viewing styles," or
"patterns of behaviour involving choices that
somehow influence attention and learning from
television" (Miron, Bryant, & Zillmann, 2001,
p. 157). Although viewing styles are related to
learning styles, this concept of different cognitive
styles is distinguished from individual learning
styles. The issue in this direction needs to be
more thoroughly researched and commented on,
because it would make it easier for advertisers to
create impactful advertisings. Other media
studies on the perception of news messages have
found that news photographs aid news
processing in a variety of positive ways.
Although support for this assumption has been
mixed in social science research (Wanta &
Roark, 1994; Mendelson, 2001; Mendelson &
Thorson, 2003), research on how people learning
from written material and images suggests that
newspaper stories and pictures are the same for
everyone as a way of perceiving but not as a way
of responding. There are assumptions about the
stronger influence of verbal elements, called
verbal anchors, among print media, as well as
greater resistance to the influence of visual
elements in electronic media products. In other
studies, the emphasis falls on visualization or
achieving effectiveness in advertising through
visual anchors. It should be pointed out that the
visualization strategy in the media space, is based
on the concept of vividness (Mittall, 1999).
Ortony, Clore and Collins found in a number of
their studies that vivid pictures as impact material
are more persuasive because they arouse
Spasova, L. / Volume 13 - Issue 73: 155-164 / January, 2024
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consumer interest (Ortony, Clore & Collins,
2011). In turn, Keller, Punam and Block
concluded that vivid information is easier for the
user to perceive and process than non-vivid
information (Keller et al., 1997), but according to
Carolyn Tripp (1997) not all advertising media
focus on the use of vivid, tangible cues (Tripp,
1997). In some cases, they rely on the content,
the story that the picture itself tells, as well as the
presence of verbal elements that attract the user's
attention and stimulate interest.
Another approach to the interpretation of
verbalization, according to information
processing, is its perception and experience as
part of contextual advertising. Assuming that one
form of verbalization describes what we
"perceive" more adequately than other
perceivers, it tells us how we convert our
"perceptions" into categories and concepts
(Forceville, 1996, p. 133). From the previous
studies, verbalization forms in advertising can be
identified as several syntactic structures and the
differences between them have been studied by
many researchers (Forceville, 1996; Mashal et
al., 2014). The researchers found, particularly
relevant to media studies, the relative
predispositions of individuals to learn from
visual and verbal materials, and how people's
"visualizing" and "verbalizing" cognitive styles
influence their response to the environment as
well as their ultimate behaviour. A high
"verbalization" user is characterized by being
word-oriented, showing high fluency with words,
preferring to read for ideas, and enjoying word
games. High “visualizers” are characterized by
being image-oriented, preferring to be shown,
and enjoying visual games such as puzzles
(Jonassen & Grabowski, 1993; Riding &
Ashmore, 1980). In earlier studies, the selection
of perceivers was made along the opposite
continuum: verbalizer/visualizer as two main
extremes, but according to more modern views
expressed by Mendelson and Thorson (2004), the
two positions are perceived as separate and
independent concepts, as not people are thought
to be only visually or only verbally inclined, but
rather show variation in both concepts
(Mendelson, & Thorson, 2004). The concept of
visual-verbal learning styles is similar to the
concept of visual and verbal literacy, although
the latter is closer to an ability, since many
scholars define visual literacy as the learned
ability to understand and interpret visual
elements (Scott, 1994). Studies in this direction
are becoming the subject of examination by
psychologists, with the goal being to explain
many individual personality traits of the learners,
as well as of the perceivers of various media
products in particular. These claims are
supported by educational research that confirms
that the presence of pictures during instruction
increases comprehension of text passages when
the accompanying pictures are appropriate to the
text (Levie & Lentz, 1982). Therefore, the
segmentation of advertising consumers into
separate groups with specific characteristics
would facilitate the understanding of the
perceived nature of verbal-visual information, as
well as provide clarity on the question of the
ultimate reactions of consumers to products and
services.
Methodology
The purpose of the present study is to segment
advertising users into several groups -
verbalizers, visualizers and, according to the
adapted and modified scale of Kirby, Moore and
Schofield (1988) - Verbalizer-Visualizer
Questionnaire (VVQ), as well as dreamers.
Another research objective is to determine how
gender and education of consumers affects the
cognitive affiliation of respondents perceiving
verbal-visual advertising information. To
achieve this goal, the Verbalizer-Visualizer
Questionnaire (VVQ) was applied as a reliable
and valid instrument for measuring cognitive
orientation. The study included 425 respondents
who answered the Verbalizer-Visualizer
Questionnaire (VVQ) to determine their
cognitive affiliation of Kirby, Moore and
Schofield’s scale, consisting of 30 statements,
with 10 statements defining high verbalizers, 10
high visualizers, and 10 high dreamers. The
research methods are related to the following
studies (Hair et al., 2003): 1) measuring the
cognitive affiliation of users by the Verbalizer-
Visualizer Questionnaire (VVQ) according;
2) segmentation of advertising consumers by
gender and education, as well as their
susceptibility to the Verbalizer-Visualizer
Questionnaire (VVQ); 3) establishing some
causal relationships between cognitive affiliation
and some demographic characteristics of the
respondents. Respondents answer all modules of
the questionnaire using a five-point Likert-type
scale, which includes ratings from 1 - Disagree to
5 - Agree. Cronbach's alpha was used to test the
reliability of an adapted and modified version of
the VVQ. The reliability of Verbalizer Scale is
α=0.722, the reliability of Visualizer Scale is
α=0.739, the reliability of Dreamer Scale is
α=0.734, For the whole sample, the Cronbach's
alpha coefficient is α=0.783. Since the values are
close to or exceed the minimum recommended
value of α=0.700 (DeVellis, 2012), the internal
consistency for the respective subscales is
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sufficiently high, i.e. the elements that compose
them form a common scale.
Results and discussion
The study was conducted in the period from
September 2022 to September 2023. Self-
reported data were collected from a total sample
of 425 respondents distributed across gender and
education age, ensuring a 95% representative
size (being e = ± 5%; p = q = 0.50). Each case
from the general population was equally likely to
be included in the study. All respondents filled in
the questionnaire on paper because this ensures
the correctness of the answers. According to
these criteria, the total sample was 39.3% male
(167 people) and 60.7% female (258 people); and
according to the education – 11.8 % (50 people)
– Secondary school completed, 39.3% (167
people) – Higher secondary school completed,
18.1 % (77 people) – Bachelor degree completed,
22.8% (97 people) – Master degree completed,
8% (34 people) – PhD completed. To determine
whether the adapted and modified scale of Kirby,
Moore & Schofield, (1988) applied in the study
was suitable for analysing the data obtained, a
confirmatory factor analysis was carried out
using a method of principal components (PCA)
and orthogonal rotation using the Varimax
method with Kaiser Normalization (Kaiser,
1974). 3 factors were determined as in the
methodology of Kirby at el., (1988), with the first
factor comprising 6 statements measuring dream
vividness, a second factor combining 6
visualization statements, and a third factor
consisting of 6 statements, measuring
verbalizers. The remaining statements, which are
of lower factor bodies and do not form a factor,
are not included in the formation of the three
factors. According to some authors, only
statements with factor weights greater than 0.500
should be analysed, that is, these are statements
with the greatest weight and should play an
important role for subsequent measurements
(Ganeva, 2016, p. 340). To ensure the fit of the
data, several well-known diagnostic checks were
performed: 1) 30 statements showed correlations
above 0.500 or higher with other items in the
VVQ; 2) The Kaiser-Meyer-Olkin (KMO)
measure of sampling adequacy was 0.697 for the
entire sample (N = 425), which is above the
recommended value of 0.600 (Kaiser, 1974).
3) Bartlett's test of sphericity was statistically
significant for all subjects (χ2 (435) = 4115.9, p <
0.000), (Bartlett, 1954). The measure of
adequacy was checked, as well as the adequacy
for each subscale of the VVQ questionnaire,
obtaining the following values: for Verbalizer
Scale KMO was 0.689; for Visualizer Scale
KMO was 0.734; for Dreamer Scale KMO was
0.612. Bartlett's tests of sphericity for each
subscale were also statistically significant for all
subjects (p < 0.000), (Bartlett, 1954).
To determine the influence of Verbalizer-
Visualizer Questionnaire (VVQ) on different
groups of respondents formed by gender, a one-
way analysis of variance (ANOVA) was applied.
The hypothesis that the arithmetic means of the
persuasive principles were different with respect
to gender was also tested, and the results of the
one-factor analysis of variance (ANOVA) are
presented in Table 1.
Table 1.
Influence of gender on susceptibility to VVQ (ANOVA)
Independent variable
Dependent variable
F
p
Mean Mean (Male) (Female)
Gender
Verbalizer Scale Visualizer Scale Dreamer Scale
F=6.87 F=0.003 F=7.39
< 0.01 p
p =0.999 p < 0.01
3.05 3.26 2.72 2.72 3.03 2.82
Results indicated that gender influenced
susceptibility to the visualization subscale and
the dreaming subscale, and overall susceptibility
to persuasion was in the hypothesized direction.
Susceptibility to visual information was achieved
to a greater extent in women compared to men,
where F=6.87; p < 0.01; x2 (women) = 3.26; x1 (male)
= 3.05, and susceptibility to information stored
through dreams is achieved to a greater extent in
males than in females, where F=7.39; p < 0.01;
x1 (men) = 3.03, x2 (women) = 2.82, (Table 1).
According to research in this direction, it can be
argued that some individuals prefer visual
information and products that emphasize the
visual, as well as others who prefer written or
verbal information. In our study, visual
information, as well as information constructed
in dreams, is essential because visual information
processing differs from verbal information
processing, as cognitive development affects the
number of revisions as well as the duration of
image fixation (Lang et al., 2002). Most of the
results obtained support this correspondence,
with researchers recommending that future
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studies focus on the relationship between
cognitive elaboration and imagery evaluation in
general. (Lang et al., 2000; Graesser et al., 2005;
Rayner et al., 2001). It should not be
underestimated that some consumers use less
verbal material and rely primarily on images
when perceiving information from various
sources, especially from an advertising medium
(Riding & Douglas, 1993). According to the
obtained results, women are shaped as better
visualizers, that is, they perceive information
visually faster, and men are better dreamers, that
is, they create pictures with dreams. Previous
studies have found that users differ in their
propensity to remember details from verbal and
visual information (Riding et al., 1995). Further
causal relationships between other demographic
characteristics and susceptibility to Verbalizer-
Visualizer Questionnaire (VVQ) should be found
in future studies.
To determine individuals' susceptibility to
verbal-visual cognitive styles shaped by
education, a one-way analysis of variance
(ANOVA) was applied. The results of the one-
way analysis of variance (ANOVA) are
presented in Table 2.
Table 2.
Influence of education on verbal-visual cognitive styles (ANOVA)
Independent variable
Dependent variable
Mean
F
p-values
Education
Visualizer Subscale
Verbalizer Subscale
Dreamer Subscale
= 3.07
(secondary school)
1
x
= 2.98
(Higher secondary school)
2
x
= 3.05
(Bachelor degree)
3
x
= 3.59
(Master degree)
4
x
=3.36
(PhD)
5
x
= 2.83
(secondary school)
1
x
= 2.63
(Higher secondary school)
2
x
= 2.89
(Bachelor degree)
3
x
= 2.57
(Master degree)
4
x
= 2.99
(PhD)
5
x
= 2.94
(secondary school)
1
x
= 3.02
(Higher secondary school)
2
x
= 2.76
(Bachelor degree)
3
x
= 2.71
(Master degree)
4
x
= 3.10
(PhD)
5
x
F=11.20
F=3.73
F=3.74
< 0.000 p
p <0.005
p < 0.005
The results show that education affects the
respondents' susceptibility to each of the
cognitive styles, with the greatest susceptibility
observed on the Visualizer Subscale, where
F=11.20; p < 0.000, and individuals with a
master's degree have the highest values - x4 (Master
degree) = 3.59. On the other subscales, it is found
that the F values are very close, such as on the
Dreamer Subscale F=3.74; p < 0.005, and the
highest values are for individuals with a doctoral
degree - x5 (PhD) = 3.10 and on the Verbalizer
Subscale F=3.73; p < 0.005, and the highest
values are for individuals with a doctoral degree
- x5 (PhD) = 2.99, (Table 2). The highest and lowest
mean values for the three subscales are
presented. Because cognitive style is an
individual's typical and consistent approach to
acquiring, processing, and organizing
information (Riding et al., 1995), it is very
important to interpret cognitive styles as
“individual variations in the way of perceiving,
remembering and thinking, or as different ways
of understanding, sorting, transforming and
using information” (Kogan, 1971, p. 244). In
addition, we all differ in the way we interact with
different information from different sources,
which is also related to the knowledge we have
acquired, argue other authors (Jonassen &
Grabowski, 1993). Therefore, in processing
information by the large inclinations of the
studied individuals to visual information for
individuals with a master degree, it is defined as
an adaptive approach in the learning processes,
because individuals with PhD show greater
inclinations to verbal information, or information
constructed at dreams. Styles themselves are
considered a subset of personality because style
is a fixed characteristic of an individual (Jackson
& Lawty-Jones, 1996). In addition, cognitive
styles differ from learning strategies, which are
defined as ways used to deal with situations and
tasks (Riding & Sadler-Smith, 1992), but they
also differ from abilities, which refer to levels of
skills (Jonassen & Grabowski, 1993). Of
particular interest in this scientific work are the
results derived from the relationship between
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cognitive style and educational affiliation,
because although they are not related to
individual abilities, they show the verbal-visual
tendencies of the examined persons in relation to
acquired education. It should not be forgotten
that our data are a snapshot of the problem at
hand, and the search for more dependencies
remains to be done in studies from different
subject areas.
In order to establish causal relationships between
gender and education the analysis of covariance
(ANCOVA) was performed. To achieve this goal
by applying an analysis of covariance
(ANCOVA), (Field, 2013) the author can have
determined whether there was a difference in
susceptibility to one of the Verbalizer Scale and
their acquired education (Kirby, Moore, &
Schofield, 1988). In this analysis, the dependent
variable is the verbalization subscale, education
is used as the covariate because it is assumed that
education and gender, measured simultaneously,
can be controlled for in the statistical analysis
when it comes to cognitive abilities. A new
variable was introduced, and the respondents
were divided according to the criterion of
education with different age characteristics:
11.8% (50 people) with secondary education
(under 18 years old); 39.3% (167 people) with
secondary special education (under 25 years old);
18.1% (77 people) with a bachelor's degree (over
25 years old); 22.8% (97 people) with a master's
degree (over 25 years old) and 8% (34 people)
with a doctoral degree (over 25 years old). The
reason for this distribution is for the covariate to
be a continuous quantitative variable. Before
performing the ANCOVA, the following
assumptions were checked: 1) checking the
correlation between the verbalization scale and
the covariate - user education as Pearson's
correlation is a weak positive correlation -
r=0.222; p<0.000, which means that the linear
relationship is less than r<0.800; p<0.000; 2) the
dependent variable is normally distributed - the
values of the coefficients for asymmetry
(Skewness) are -0.532, and for (Kurtosis)
kurtosis are -0.342, that is, relatively close to
zero, (Ganeva, 2016); 3) homogeneity of
variation, i.e. similar variations were observed
across groups. Before proceeding with an
analysis of covariance (ANCOVA), it is
necessary to present the means for the Verbalizer
Subscale and education, before accounting for
the interaction effect. Means before analysis of
covariance (ANCOVA) are presented in Table 3.
Table 3.
Mean of Verbalizer Scale and education of respondents
Verbalizer Subscale /
Education
Means
N
Std.
Deviation
Male Secondary school
Higher secondary School
Bachelor degree
Master degree
PhD
Female Secondary school
Higher secondary School
Bachelor degree
Master degree
PhD
Mean= 2.82
Mean =2.60
Mean= 2.69
Mean= 2.88
Mean= 2.84
Mean= 2.85
Mean= 2.65
Mean =3.00
Mean= 2.47
Mean= 3.11
28
72
27
25
15
22
95
50
72
19
0.725
0.694
0.581
0.743
0.704
0.980
0.835
0.940
0.586
0.807
Male respondents with a master's degree and
female doctoral respondents had the highest
means: Mean=2.88 and Mean=3.11 on the
Kirby et al. (1988) Verbalizer Subscale, with
similar standard deviations, indicating that the
subscale in each group is equally dispersed. It
is assumed that the education of the
respondents with different age characteristics
can be influenced by the gender of the subjects
on the measured subscale, therefore a
covariance analysis (ANCOVA) is applied.
The results of the analysis of covariance are as
follows: Levene's test is statistically
insignificant - p=0.318, which indicates that
the group variances are equal and the
assumption of homogeneity of variance is not
violated (Ganeva, 2016); The results of the
analysis of covariance (ANCOVA) are
presented in Table 4, (Table 4).
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Table 4.
Influence of gender on Verbalizers Scale according to education (ANCOVA)
Verbalizer Subscale
df
Mean Square
F / p-values
Partial Eta Squared
Gender Education Gender/Education Error Total
1 4 4 415 425
0.162 1.366 1.399 0.584
F=0.277; p= 0.599 F= 2.34; p < 0.05 F=2.39; p < 0.05 Adju. R Squared =
0.052.
0.01 0.22 0.23
A statistically significant interaction effect of
respondents' gender and education was found on
the Verbalizer Subscale, where F (4,415) = 2.39,
p < 0.05, eta = 0.23, which according to Cohen
(1988) is a medium effect size. The Partial Eta
Squared results indicated that more than 2% of
the variance of the dependent variable -
Verbalizer Subscale was predicted by education,
with Adjusted R Squared = 0.052, (Table 4). The
two independent variables were analyzed
separately and the main effect for the
independent variable gender was not statistically
significant F (1,424) =0.277, p< 0.599 in the
analysis of covariance (ANCOVA), i.e. there was
no statistically significant difference when the
Verbalizer Subscale was applied by gender. The
main effect for the other independent variable –
education was statistically significant, where F
(4,415) = 2.34, p < 0.05, because there was a
statistically significant difference in the
measurement of Verbalizer Subscale by
education. Cohen's interpretation of eta, 0.24 ≤ η
< 0.37, indicated that a weak effect size value
was observed, eta = 0.22. After performing the
analysis of covariance, the adjusted means for the
study groups are presented in Table 5, controlling
for the covariate – education with age difference,
(Table 5).
Table 5.
Adjusted means for Verbalizers Subscale controlling for the covariate (ANCOVA)
Verbalizer Subscale / Education
Means
Std. Error
Male Secondary school
2.82 =
Mean
0.144
Higher secondary School Bachelor degree Master degree PhD
Mean=2.60 Mean=2.69 Mean=2.90 Mean=2.84
0.090 0.147 0.153 0.163
Female Secondary school
Higher secondary School
Bachelor degree
Master degree
PhD
Mean=2.85 Mean=2.65 Mean=3.00 Mean=2.57 Mean=3.15
0.078
0.108
0.109
0.090
0.175
After analysis of covariance (ANCOVA) it is
found that male and female with master degree
have an interaction effect, with the mean values
for men being - Mean=2.90 and for women -
Mean=2.57, therefore the effect is greater for
male with Master degree relative to women of the
same group. The second interaction effect is for
respondents with a doctorate degree, with the
average values for men being - Mean=2.85 and
for women - Mean=3.15, therefore the effect is
greater for women with master degree than men
of the same group, (Graph 1). The results showed
that susceptibility to the Kirby et al. (1988) -
Verbalizer Subscale was determined by gender,
with the intersection of the arithmetic means of
users with a master's degree and a doctorate
confirming an interaction effect when combined
measuring respondents' education, (Graph 1).
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Graph 1. Susceptibility to Verbalizer Subscale on gender and education.
The significance of the latter measure indicates
that gender as a factor can determine
susceptibility to the Verbalizer Subscale only
when the subjects' education is also taken into
account. Such statistical significance could not
be established by the one-way analysis of
variance (ANOVA) that was performed on the
gender distribution. These results confirm the
findings of other researchers who indicate that
verbalization in all its dimensions: "verbal
anchors," (McQuarrie & Phillips, 2005)
"documentation," (Mattila, 2000) "verbalization
styles on memory" or "styles of cognitive
verbalization,"cognitive user preferences,"
(Kirby, Moore, & Schofield 1988) "verbal
structures" (Phillips, 2000), is associated with
certain semantic operations, because they have
different interpretations among individual users,
and education is also measured in our analysis.
Establishing a relationship between different
factors characterizing individuals when
processing verbal components can contribute to
a more accurate understanding of the processes
taking place when processing verbal information.
In addition, researchers find a relationship
between visual metaphors and verbal structures
in advertisings because the former aid the
perceived essence of the latter in individuals'
interpretation of information (McQuarrie &
Phillips, 2005).
Conclusion
In the processing information, researchers very
often look for dependencies between the
cognitive affiliation of individuals and their final
reactions to verbal-visual information. The
present study attempted to segment respondents
into verbalizers, visualizers, and dreamers,
finding that on the Verbalizer-Visualizer
Questionnaire (VVQ), and female respondents
are susceptible to the Verbalizer Scale, and male
respondents are susceptible to the Dreamer Scale.
No statistically significant results were found on
the Visualizer Scale. Therefore, women process
verbal information in advertising more easily,
and men respond positively to information that is
induced by the vividness of the dream. When
segmenting users according to the criterion of
education, it was found that highly visual
abilities are possessed by individuals with a
master's degree, and verbal by users with a
doctoral degree, that is, with an increase in
educational abilities in various qualification and
scientific fields, respondents show verbal
abilities more than visual abilities. On the
subscale measuring dream vividness, the biggest
dreamers again appeared to be advertising
consumers with doctoral degree.
The researcher of the present scientific paper also
made additional measurements, and different
solutions were sought, but a statistically
significant result was found when measuring
respondents' gender and education at the same
time, inferring susceptibility to the Verbalizer
Scale. Male advertising consumers with a
master's degree are more susceptible to the
Verbalizer Scale than female advertising
consumers of the same degree. The second
interaction effect was female with doctoral
degree respondents who were most receptive to
the Verbalizer Scale relative to all other target
groups. The significance of the latter measure
indicates that gender as a factor can determine
susceptibility to the Verbalizer Subscale only
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/ January 2024
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when the subjects' education is also taken into
account. These results confirm the findings of
other researchers who indicate that verbalization
in all its dimensions: verbal anchors,
documentation, verbalization styles on memory
or styles of cognitive verbalization, cognitive
user preferences, verbal structures, is associated
with certain semantic operations because have
different interpretations among individual users,
and education is also measured in our analysis. In
our study, a strong response was observed on the
part of men with a master's degree and women
with a doctorate degree to verbal information.
These scientific results can serve many
advertising researchers, some marketers, as well
as cognitive psychology and communication
specialists to properly segment advertising
consumers.
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