European Journal of Education Studies
ISSN: 2501 - 1111
ISSN-L: 2501 - 1111
Available on-line at: www.oapub.org/edu
10.5281/zenodo.163257
Volume 2│Issue 7│2016
INVESTIGATING THE ASSOCIATION BETWEEN TURKISH
FRESHMAN’S MULTIPLE INTELLIGENCE PROFILES AND
UNIVERSITY ENTRANCE EXAM PERFORMANCE
Sait Atas1i, Yavuz Erisen2
Faculty of Education, University of Ottawa, Ottawa, Ontario, Canada
1
Faculty of Education, Yildiz Teknik University, Istanbul, Turkey
2
Abstract:
Even though curriculum designers in Turkey considered Gardner’s multiple
intelligence theory as one of the most important theories during the curricula reform in
2005, the university entrance examination system is still on the basis of the two
intelligence areas only, mathematical-logical and linguistics intelligence. The aim of this
study was to investigate the relation between students’ multiple intelligence profiles,
gender, and the university entrance exam performance. Results of the study indicated
that linguistic and logical-mathematical intelligences were the most dominant
intelligence areas of the participants. Also, there was a statistically significant difference
in participants’ dominant intelligence areas with respect to gender and the university
entrance exam scores. Findings from this study suggest reconsiderations in using only
one examination to guide students with different abilities and skills through career
options and provide insights into considering alternative ways of university entrance
exams that may move beyond only measuring linguistic and mathematical
intelligences.
Keywords: multiple intelligence; guidance; career choice; university entrance exam;
curricula reform
Introduction
Determining skills and interests enables one to find the most appropriate career
options. Finding a qualified match between skills and career orientation is an important
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Published by Open Access Publishing Group ©2015.
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PROFILES AND UNIVERSITY ENTRANCE EXAM PERFORMANCE
factor on improving productivity in workplaces. As Aydin (2008) stated that students
need to be educated at as early an age as possible in order to make favourable and
appropriate decisions in regards to their career choices. Furthermore, any educational
system needs to take into account students’ individual differences with respect to
abilities and types of intelligence in guiding students through career orientation (Arslan
& Kilic, 2008: Erisen, 2001). However, guiding students through career orientation
seems to be problematic with respect to considering their individual unique abilities
(Akkok, 2003).
Most people around the world consider getting acceptance to college or
university as a good start to a professional career path. In this regard, standardized
testing plays an increasingly important role in the university admissions process for
some countries. All four-year undergraduate programs in Europe require university
entrance exams for admission. However, in this system of placement, there is no effort
made to consider student interests, needs, and in general his/her individual differences.
A review of the system of university admissions in Turkey reveals that there is a similar
trend in Turkey as in other European countries.
Overall, university entrance exams in Turkey measure: 1) students’ ability to
apply problem solving skills to routine problems in different areas such as mathematics,
science, and 2) knowledge of high school curriculum in Turkish literacy history,
geography, and philosophy. A closer look at the university entrance system in Turkey
will be presented below.
University Entrance System in Turkey
The Student Selection Examination (SSE)ii is a standardized exam in Turkey used for
determining admission to higher education. The Student Selection and Placement
Center (SSPC)iii has administered this exam since 1974. Initially in the 1970s, SSPC
administered one single exam. The mark received in this examination was averaged out
with the student’s high school GPA (ÖSYM, 2009). In the subsequent years, the number
of stages in the examination system varied between one and two exams from year to
year. For instance, while there was only one required exam for university entrance
between the years 1999-2009, beginning in 2010, students now need to take two exams
and pass the predetermined minimum score to be able to enter university or a college.
Basically, these two exams covers topics from different subject matters taught in
Student Selection Examination(SSE) is English translation for, Ögrenci Secme Sinavi(ÖSS)
Student Selection and Placement Center (SSPC) is English translation for Ögrenci Secme ve Yerlestirme
Merkezi (ÖSYM)
ii
iii
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different levels of high school. For the first stage, students take the Transition to Higher
Education Examination (HEE)iv every April. In the HEE examination, students are
required to answer 160 multiple choice questions from different subjects, including
Turkish, math, and social and natural sciences in 160 minutes. Those who obtain a
passing mark on the HEE (i.e., 140 points out of 500) proceed to take the Undergraduate
Placement Examination (UPE)v in June. The UPE has five subsections including foreign
language, mathematics, social sciences, literature, and the sciences including biology,
chemistry, and physics. Each subsection is evaluated individually and a standard score
is calculated for each subject. The minimum total score for five subjects is 180 and the
maximum score is 500. A final score is calculated by adding 40% of the HEE, the first
stage exam, score and 60% of the UPE, the second stage exam. Students also get extra
points depending on their high school grade point average (GPA). Students who score
at least 180 in UPE exams are able to rank their decisions for specific undergraduate
degree programs (ÖSYM, 2010).
Overall, one of the most prominent criticisms to the university entrance
examination in Turkey relates to the system’s attempt at measuring only two
intelligence domains of students, which are linguistic and mathematical-logical
intelligences (Celikoz et al., 2008). As an example, in order to get admission to science
related majors, students need to score higher in mathematics and science. Conversely,
students need to score higher in social sciences to get into majors related to social
sciences. Thus, it is almost impossible for a student to get acceptance from a university
without demonstrating a certain level of linguistics and analytical abilities and skills
because solving questions in the exam only requires different variations of these two
main skills. That is said, students’ performance on the examination limits their choices
of majors. For instance, according to the results of the study by Sarikaya and Khorshid
(2009), 34.4% of newly enrolled undergraduate students indicated that they had
enrolled in one of the majors at the university based on their exam scores, and that they
would have preferred another major based on their unique abilities if they could have
done so. An analysis of the university entrance system demonstrates that university
admissions offices hold an assumption on there being a significant correlation between
university entrance exam scores of high school graduates and their achievement in
university or college. However, this assumption is based on the misguided foundation
of the traditional approach to human intelligence, which claims the ability to solve
Transition to Higher Education Examination (HEE) is English translation for Yuksek Ogretime Gecis
Sinavi (YGS)
v Undergraduate Placement Examination (UPE) is English translation for Lisans Yerlestirme Sinavi (LYS)
iv
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logical and mathematical problems as being the most important factor of intelligence
(Topses, 2003; Yavuz, 2004).
This approach to human intelligence expects all students to demonstrate
different characteristics of mathematical-logical intelligence and guides students
through career choices based on the variations of one typical intelligence. However,
‘individuals might have different capacities in different areas and differ from one
another in their ability to understand complex ideas, to adapt effectively to the
environment, to learn from experience, to engage in various forms of reasoning, to
overcome obstacles by taking thought’ (Neisser et al., 1996, p. 77).
Theoretical Framework
Howard Gardner, a psychologist of Harvard University, challenged the conventional
idea of human intelligence by asserting that human cognitive competence is better
described as a ‘set of abilities, talents, or mental skills, which are referred to as
intelligence’ (Gardner, 1993, p. 15). He has proposed the Multiple Intelligences (MI)
Theory which introduces the idea that every individual has at least eight types of
intelligences (Gardner, 1983). According to the theory, initially there were seven
different and independently working intelligence areas (Gardner, 1983), to which he
added an eighth intelligence area (Gardner, 1999). These areas are: (1) linguistic, (2)
logical-mathematical, (3) musical, (4) spatial, (5) inter-personal, (6) bodily-kinesthetic,
(7) intra-personal, and (8) naturalistic intelligencevi.
As stated by Gardner, each individual was born with having different levels of
the previously mentioned eight intelligence areas and these areas can improve
throughout life. Every person can have one or more areas of intelligence which are
more advanced than another. A person’s initial weak skills in an area of intelligence can
later become his/her dominant area of intelligence (Gardner, 1993).
Shearer (2004)
highlights that it is possible, for example, that a person can have extraordinary
linguistic intelligence, but low intelligence in music. To that effect, it is the
responsibility of educators to prepare students by carrying out activities that cater to
students’ specific strengths and needs while designing instruction (Tomlinson, 2014). In
general, if teachers are careful to design instructions through the use of all types of
intelligences to the extent they can, they would be able to support students who are
good at certain intelligences but also to help students who need to improve some
intelligence areas.
vi
For a detailed description of the different intelligence areas please see Gardner, 1993.
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This Study
The Ministry of National Education (MoNE) in Turkey re-designed the curricula based
on the new theoretical developments in the field of education in 2005. Gardner’s MI
theory was one of the considerations in order to help students develop all eight
intelligence areas in schools. However, even though curriculum developers regarded
Gardner’s theory as one of the most important theoretical bases, as discussed before, the
university entrance examination in Turkey still only measures two dimensions of
intelligence (i.e., mathematical-logical and linguistic intelligence) in applying Gardner’s
theory (Pehlivan, 2008). In other words, the Ministry of National Education in Turkey
has been encouraging teachers at elementary, secondary, and high school levels to
diversify their activities in classrooms based on multiple intelligence theory since 2005.
Thus, students can have educational opportunities to develop all eight areas of
intelligences. However, when it is time to assess students’ different abilities and skills to
determine their career path, students are assessed based on only two types of
intelligence. That is said, students are guided based on only two dimensions of multiple
intelligences at the end of high school. Therefore, first, a valid MI scale was used to
determine first year undergraduate students’ intelligence profiles in this study. Then,
the relation between students’ intelligence profiles and their exam scores from the
university entrance examination, which is a main factor in determining their career
path, was examined to explore entrance exam’s capability to place students in an
undergraduate degree according to their different multiple intelligence areas.
Finally, researchers of this study also examined the difference between female
and male students’ multiple intelligence profiles to explore possible differences in terms
abilities and skills as MI theory strongly advices to organize educational settings based
on individual differences derived from gender, differing ability and skills.
This study addressed the following research questions:
1. How do undergraduate students’ multiple intelligence profiles vary?
2. Is there a statistically significant difference between first year female and male
undergraduate students’ mean level of intelligence in each area?
3. Is there a statistically significant difference between first-year undergraduate
students’ MI profiles and their scores from university entrance examination
system?
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Methodology
A non-experimental correlational research design was used to describe the statistical
association between first-year undergraduate students’ MI profiles, gender and scores
from the university entrance examination system in Turkey.
Participants
The participants of this study were 245 first-year undergraduate students from a public
university in Turkey. Participants were randomly selected from eight different faculties
of the university including the Faculty of Communication Studies, Faculty of Art,
Faculty of Science, Faculty of Religious Studies, Faculty of Engineering, Faculty of
Agricultural Studies, Faculty of Language and Literature Studies, and Faculty of Health
Sciences.
Data Collection Tool and Procedure
An ordinal ‘Multiple Intelligence Profile Scale’ (i.e., the MI scale) was used to determine
students’ MI profiles as conceptualized by Gardner. According to developers of the
scale, Celikoz et al. (2008), the MI scale was completed by a wide-ranging sample of 228
faculty members from different fields of universities and over 965 students in order to
establish reliability and content validity of the scale. The MI scale consists of 11 subdimensions which involve different daily life situations as follows; (1) spare time
activities, (2) courses, (3) learning methods, (4) different abilities or skills (5) devices and
materials mostly used in daily life, (6) games, (7) occupations, (8) most disturbing social
problems, (9) places to visit, (10) daily activities, and (11) likes/dislikes. Further, each
sub-dimension involves 8 items each of which represent one of the eight intelligence
areas from the MI theory. For example, items for the spare time activities subdimension involve reading, listening to music, drawing or painting, solitariness,
watching movies, playing with computers, doing sports, and spending time with pets.
In the spare time activities sub-dimension, reading represents linguistics intelligence,
listening to music represents musical intelligence, drawing/painting represents spatial
intelligence, playing with computer represents logical-mathematical intelligence,
solitariness represents intra-personal intelligence, chatting represents inter-personal
intelligence, and exercise represents bodily-kinesthetic intelligence.
The MI scale starts with a brief instruction on its first page followed by a sample
rating task and then asks participants to complete the scale accordingly. The instruction
and sample task are as follows:
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Dear students,
This scale is intended to determine your skills. Please choose each situation that
describes you best. Otherwise, there will be problems in identifying your skills.
Therefore, do not leave any question blank, read each question carefully and choose the
appropriate answer. Rank each question according to how the situation suits you (1
being the most approprıate, 8 being the least appropriate).
Mary is a 6th grade student. She enjoys spending her spare time with animals.
She does not like to be alone. She also enjoys going to the movies, playing on the
computer, and listening to music. She does not enjoy reading books and sports much.
Mary ranked her likes as follows:
( 6 ) Reading
( 5 ) Listening to music
( 4 ) Drawıng/painting
( 8 ) Solitariness
( 2 ) Movies
( 3 ) Computers
( 7 ) Sports
( 1 ) Pets
Like Mary did, please answer the questions below ranking them from 1 to 8 (1 being the most
liked, 8 being the least liked.)’
Following the instructions, students were then asked to rate their preferences of
given 8 items in each sub-dimension, ranking them from 1 to 8 based on the amount of
time they spend doing or how much they like/dislike each particular item. A detailed
description of how students multiple intelligence was determined based on the
rankings will be presented below in the data analysis section of this paper.
In order to examine the reliability of the MI scale, Cronbach alpha (α) scores
were calculated for each sub-dimension in the scale using test-retest techniques.
Cronbach’s alphas for the 8 sub-dimensions were as follows: linguistic intelligence
(α=.92), logical-mathematical (α=.95), musical (α=.98), spatial (α=.95), inter-personal
(α=.90), bodily-kinesthetic (α=.92), intra-personal (α=.90), and naturalistic (α=.91).
Further, in order to establish construct validity of the scale, the researchers consulted
expert opinions from different fields including psychology and educational
measurement and assessment. Overall, experts went through the items and situations
included in the MI scale and indicated that each situation and eight items under each
situation covered in the scale were valid indicators of the each type of multiple
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intelligences (Celikoz et al., 2008).Results from the study indicated that the MI scale is a
highly reliable and valid measure of undergraduate students’ multiple intelligence
profiles.
Data Analysis
Descriptive statistics for all the variables were computed as well as checks for
underlying assumptions of the subsequent analyses, such as normality and
homogeneity of variances. In order to examine participants’ most dominant intelligence
areas with respect to their individual differences such as gender, declared major, and
scores obtained from the university entrance exam, frequencies (f), percentages (%),
means ( ̅ ), and standard deviations (sd) were calculated.
As indicated earlier, raw ratings were collected from students for the 88 items
under 11 sub-dimensions. Different scores were created based on these raw rankings in
order to obtain a total score for each participant’s intelligence area, as described below.
These raw rankings were recoded into different scores from 1 to 8 because raw ratings
by participants do not reflect the true priority of participants’ choices. For example, if a
participant ranks music as 8 for the most enjoyed courses, that mean the participant
favours other courses over music, thus s/he gives an 8 to music among the most enjoyed
courses. Conversely, if a participant ranks library as 1 for the most desirable visiting
places, that indicates that this person likes libraries the most among other possible
visiting places. Therefore, each rating for the 88 items was assigned a different score
both to reflect true order of choices and to obtain total scores for each intelligence area.
With this regard, ranking 8 was coded as 1, ranking 7 was coded as 2, ranking 6 was
coded as 3, ranking 5 was coded as 4, ranking 4 was coded as 5, ranking 3 was coded as
6, ranking 2 was coded as 7, ranking 1 was coded as 8. Possible scores for each
participant in each intelligence area ranged from 11 to 88 with a midpoint 49.5. Higher
scores of intelligence areas indicate higher levels of dominance. The area with the
highest score was identified as the person’s preferred Multiple Intelligences area. Thus,
a participant’s most dominant intelligence can be determined.
To illustrate, suppose that a participant’s ranking for the items represents
musical intelligence under eleven sub-dimensions as follows; s/he ranks listening to
music as 5 among the eight spare time activities, ranks music as 4 for the most enjoyed
courses, ranks melody/rhythm as 6 for the mostly used learning methods, ranks singing,
playing a musical instrument as 6 for the most talented area, ranks musical instrument as 7
for the most frequently used items, ranks dancing as 8 for the mostly like games, ranks
singer as 5 for the most interesting occupations, ranks bad music as 8 for the most
concerned social and global issues, ranks concert as 1 for the most desirable visiting
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place, ranks song writing as 2 for the easiest activities, and ranks noises/melodies as 7 for
the least likes. As described earlier, these ratings were converted into different scores, in
order, 4, 5, 3, 2, 1, 8, 7, 2. Then, this participant’s musical intelligence score would be the
sum of these converted ratings as being 32.
T-test and One Way Analysis of Variance (ANOVA) tests were conducted on the
participants’ total score for each intelligence domain in order to determine if there is a
significant difference between students’ dominant intelligence areas with respect to
gender, declared major, and university exam scores. Moreover, the Scheffe test was
conducted as a follow up test to describe any further significant difference in terms of
dominant intelligence area.
Result and Discussion
1. How do undergraduate students’ multiple intelligence profiles vary?
Descriptive statistics were calculated in order to determine first year undergraduate
students’ multiple intelligence levels. While Table 1 presents the total number of
participants (N), mean scores ( ̅ ) for each intelligence area, standard deviation (sd) of
these scores, minimum (min.) and maximum scores (max.) obtained by participants in
each intelligence area. As seen in Table 1, linguistic intelligence has highest mean
among other intelligences (M=56.66, SD=12.82) followed by logical-mathematical
intelligence (M= 52.55, SD=12.52) while naturalistic intelligence has the lowest mean
(M=40.67, SD=10.22) among the participants of this study.
Table 1: Participants’ level of multiple intelligence profiles
Intelligence Areas
N
sd
Min.*
Max.*
Linguistic Intelligence
245
56.66
12.82
20.00
82.00
Musical Intelligence
245
49.68
15.87
20.00
88.00
Spatial Intelligence
245
48.68
12.53
16.00
80.00
Intra-personal Intelligence
245
50.54
11.54
18.00
80.00
Inter-personal Intelligence
245
50.20
9.8
16.00
78.00
Logical-mathematical Intelligence
245
52.55
12.52
22.00
80.00
Bodily-kinesthetic Intelligence
245
47.16
14.30
12.00
84.00
Naturalistic Intelligence
245
40.67
10.22
15.00
65.00
Table 2 also shows the percentage of participants who declared each intelligence area as
the most dominant area. In order to help us understand the declared level of each
intelligence area better, five categories including very low, low, medium, high, and very
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high, were created by equally dividing the interval between possible lowest score (i.e.,
11.00) and possible highest score into five. As seen in Table 2, the percentages of
participants who declared each intelligence as being high as follows: linguistic
intelligence (47.3%), logical-mathematical (37.6%), intra-personal (29%), musical
(25.7%), bodily-kinesthetic (24.1%), spatial (23.7%), inter-personal (20.8%), and
naturalistic (6.1%). Moreover, 60% of participants declared their inter-personal
intelligence area as being medium, while 58.8% of participants believed that their
naturalistic intelligence is at low level.
Table 2: Percentages of participants with each intelligence area as most dominant
Multiple Intelligences
N
high
medium
low
Linguistic Intelligence
245
47.3
37.6
15.1
Musical Intelligence
245
25.7
36.7
37.6
Spatial Intelligence
245
23.7
42.4
33.9
Intra-personal Intelligence
245
29.0
50.2
20.9
Inter-personal Intelligence
245
20.8
60.0
19.2
Logical-mathematical Intelligence
245
37.6
37.5
24.9
Bodily-kinesthetic Intelligence
245
24.1
34.7
41.2
Naturalistic Intelligence
245
6.1
35.1
58.8
Very Low
11.00 - 26.40
Low
26.41 - 41.80
Medium
41.81 - 57.20
High
57.21 - 72.60
Very High
72.61 - 88.00
Considering participants’ intelligence profiles revealed in Table 1 and 2, the dominance
of linguistic and logical-mathematical intelligence areas among freshman might be due
to the fact that these two intelligence areas are the most valued domains in the Turkish
educational system. Particularly, questions are formed only based on these two
intelligence areas in the university entrance exam in Turkey which sets a barrier
between students and career path. High school students need to demonstrate their
knowledge and skills related to linguistics and logical-mathematical intelligence areas
upon graduation of high school in order to enter a university or college regardless of
their choice of major. The possibility of entering a university or college increases if
students develop their skills related to linguistics and logical-mathematical intelligence.
Moreover, the dominance level of all intelligence areas among participants ranged
around ‘medium’ level with mean scores differing between 41.81 and 57.20 except for
the naturalistic intelligence being at ‘low’ level. However, this area is also close to
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‘medium’ level. Furthermore, the bodily-kinesthetic intelligence area has the lowest
minimum scores and the logical-mathematical intelligence area has the highest
minimum scores. These findings are consisted with Armstrong’s (2000) conclusion that
every individual possesses all intelligence areas at various levels, however some
individuals have high intellect in particular areas. Additional support for this line of
inquiry can also be found in the work of Celikoz (2009) and Hamurcu et al. (2011).
While examining university students’ multiple intelligence profiles with respect to
different variables, Celikoz (2009) and Hamurcu et al. (2011) also found that university
students’ multiple intelligence levels are at medium level for all intelligence areas.
2. Is there a statistically significant difference between first year female and male
undergraduate students’ mean level of intelligence in each area?
A t-test was conducted to answer the second research question, is there a statistically
significant difference between first year female and male undergraduate students’ mean
level of intelligence in each area? Table 3 below presents the t-test results related to
participants’ dominant intelligence areas by gender.
Table 3: Participants’ multiple intelligence levels by gender
Intelligence Area
Linguistic
Musical
Spatial
Intra-personal
Inter-personal
Logical-mathematical
Bodily-kinesthetic
Naturalistic
Gender
N
sd
Male
109
54.28
13.06
Female
136
58.57
12.35
Male
109
48.35
16.38
Female
136
50.75
15.43
Male
109
46.42
11.79
Female
136
50.49
12.85
Male
109
49.98
10.94
Female
136
50.99
12.02
Male
109
49.46
10.30
Female
136
50.79
9.38
Male
109
54.65
12.24
Female
136
50.86
12.53
Male
109
51.70
14.48
Female
136
43.52
13.11
Male
109
41.17
10.31
Female
136
40.28
10.18
t
P
2.629
0.009*
1.178
0.240
2.556
0.011*
0.676
0.500
1.060
0.290
2.377
0.018*
4.629
0.001*
0.673
0.502
P<0.05 (*) Asterisk indicates significant difference at 0.05 alpha level
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As depicted in Table 3, there is a significant difference between female and male
participants’ distributions of intelligence levels in the linguistics, spatial, logicalmathematical, and bodily-kinesthetic areas. Specifically, there was a statistically
significant difference in the mean scores of the linguistics intelligence for male
(M=54.28, SD=13.06) and female participants (M=58.57, SD=12.35); t=2.629, p=0.009; and
mean scores of the spatial intelligence for male (M=46.42, SD=11.79) and female
participants (M=50.49, SD=12.85); t=2.556, p=0.011; mean scores of the logicalmathematical intelligence for male (M=54.65, SD=12.24) and female participants
(M=50.86, SD=12.53); t=2.377, p=0.018; and mean scores of the bodily-kinesthetic
intelligence for male (M=51.70, SD=14.48) and female participants (M=43.52, SD=13.11);
t=4.629, p=0.001. While female participants’ mean scores for the linguistics and spatial
intelligences are higher than male participants, male participants’ mean scores for the
logical-mathematical and bodily-kinesthetic intelligences are higher than female
participants.
These results are consistent with the gender expectations and gender roles
prospected for individuals in the Turkish society. One would expect male participants
to have higher bodily-kinesthetic intelligence scores than female participants in the
Turkish society due to an assumption that male individuals are more likely to engage in
occupations that require use of physical power and muscles. It is also believed in the
Turkish society for male individuals to take responsibility over accounting duties of the
family, such as calculating monthly total income and expenses of the family. These
kinds of responsibilities of male participants would provide them with more
opportunities to improve
their mathematical-logical intelligence than female
participants. Thus, the results of this study indicating higher mathematical-logical
intelligence scores for male participants compared to the female counterparts are
consistent with expectations and responsibilities accepted by the Turkish society.
Furthermore, female participants’ higher linguistic and spatial intelligence scores are
also consistent with the general assumptions related to female individuals’ roles and
responsibilities in the Turkish society. First, it is believed in the society that women
have a better ability than men to express ideas and feelings. Second, there is a common
assumption that interior design and organization of the home life become important
parts of the female individual’s daily life. Due to these two assumptions related gender
roles and responsibilities; one would expect female participants of this study to have
higher linguistics and spatial intelligence scores than male students. Moreover, studies
of the societal views on gender roles in Turkey have also supported these findings. For
example, a recent report published by UNESCO in 2010 highlighted that Turkey needs
to do much more to overcome inequalities based on gender. As indicated in the report
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7% of girls between ages 8 and 12, never enroll to school while the percentage is only
2% for boys of the same age group in Turkey. By age 15, female attainment is about 20%
below than male enrolment (UNESCO, 2010). According to Caner et al. (2015) the
cultural bias against the education of girls is a crucial element in explaining low
educational attainment of girls. The researchers also reported that parents’ traditional
view on roles and responsibilities of girls was the main reason for not educating girls
while having a parent with a traditional view does not have an impact on the
educational attainment of boys. In another study by Adana et al. (2011), 54.3% of
undergraduate male students believe that women in Turkish society is responsible only
for the organization of home life, giving birth to children, looking after the elderly
members of the house.
Studying secondary school students’ multiple intelligence profiles in different
cultures, the findings reported by Shahzada, Khan, and Ghazi (2015) also indicated that
female students had higher linguistic intelligence scores than their male counterparts,
while male students had higher naturalistic bodily/kinesthetic and naturalistic
intelligences than their female counterparts. Similarly, Furnham and Budhani (2002)
reported
that
male
participants
scored
higher
on
visual/spatial
and
logical/mathematical intelligences, while female respondents scored higher on
intrapersonal and musical intelligences.
3. Is there a statistically significant difference between first-year undergraduate
students’ MI profiles and their scores from university entrance examination
system?
In Turkey, high school graduates receive three different scores in the university
entrance exam depending on their performance on different stages of the exam. The
three types of scores obtained from the exam are linguistics, mathematical and
combined scores. The linguistics score is assigned based on students’ performances in
the linguistics related questions that measure language abilities and the mathematical
score is given based on students’ performances in the mathematical related questions to
measure analytical ability of students. Moreover, a combined score is given as a
combination of linguistics and mathematical scores. Then, students are placed in an
undergraduate degree based on one of the three scores of their choice depending on the
ranking of their preferences, as different faculties/majors require a different score from
the university entrance exam. Considering the participants of this study, for example,
while getting admission from the Faculty of Language and Literature Studies and
Faculty of Art require higher linguistic scores, getting admission from the Faculty of
Science, Faculty of Health Sciences, and Faculty of Agricultural Studies requires higher
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mathematical scores. Similarly, getting acceptance from majors in the Faculty of
Communication Studies require higher combined scores.
As seen in Table 4 below, 138 participants of this study were placed in an
undergraduate major based on their linguistics scores while 85 of them were placed
based on their mathematical scores and 22 of them were majoring based on their
combined scores. Hypothetically speaking, if the university entrance exam is really
good at placing high school graduates in majors according to students’ diverse
intelligence areas, one would expect from the results of this specific analysis that
participants who were placed in an undergraduate program based on their linguistic
scores would have the mean level of linguistic intelligence highest among eight types of
intelligence. Likewise participants majoring in one of the undergraduate program based
on their mathematical scores would have the mean level of their mathematical
intelligences highest among other types of intelligences. Similarly, same logic would
apply to the expected intelligence areas of the other faculties.
One-way analysis of variance (ANOVA) was run for each intelligence area to
determine whether there is a statistically significant difference between participants'
mean scores on each declared intelligence area with respect to scores in the university
entrance exam as a main determinant of participants’ majors in the university. For each
ANOVA, three different types of exam scores served as independent variable while the
mean scores for each intelligence was the dependent variable. The table below shows
eight different one-way ANOVA tests results.
Table 4: One-way ANOVA results showing the comparison of participants’ dominant
intelligence areas with the university entrance exam scores
Intelligence Area
Score
Linguistics
Linguistic
Musical
Spatial
Intra-personal
N
ഥ
࢞
sd
138
58.70
12.64
Mathematical
85
54.16
12.11
Combined
22
53.55
14.78
Linguistics
138
47.12
12.46
Mathematical
85
52.40
19.03
Combined
22
55.23
19.00
Linguistics
138
49.90
11.79
Mathematical
85
44.65
12.22
Combined
22
56.64
13.32
Linguistics
138
52.58
10.24
Mathematical
85
48.66
12.33
Combined
22
45.00
13.47
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F
p
4.009
0.018*
4.508
0.012*
10.215
0.001*
6.060
0.003*
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Linguistics
Inter-personal
Logical-mathematical
Bodily-kinesthetic
Naturalistic
138
50.34
8.66
Mathematical
85
50.54
10.94
Combined
22
48.00
11.93
Linguistics
138
49.27
11.63
Mathematical
85
58.35
11.43
Combined
22
50.68
14.39
Linguistics
138
47.33
15.20
Mathematical
85
47.18
13.38
Combined
22
46.05
12.32
Linguistics
138
40.96
9.35
Mathematical
85
40.16
11.34
Combined
22
40.86
11.31
0.618
0.540
15.824
0.001*
0.076
0.927
0.161
0.852
P<0.05 (*) Asterisk indicates significant difference at 0.05 alpha level
As presented in Table 4, there were statistically significant differences in the mean
scores of participants some intelligence areas with respect to the different exam scores
used to place students in undergraduate programs. Post hoc comparisons using the
Tukey HSD test indicated that the mean score for the linguistics intelligence (F=4.099;
p<0.05) was significantly different with respect to linguistics scores, musical intelligence
(F=4.588; p<0.05) was significantly different with respect to combined scores, spatial
intelligence (F=10.215; p<0.05) was significantly different with respect to combined
scores, intra-personal intelligence (F=6.060; p<0.05) was significantly different with
respect to linguistics scores, and mathematical-logical intelligence (F=15.824; p<0.05)
was significantly different with respect to participants’ mathematical scores from the
university entrance exam.
Participants who were enrolled in an undergraduate program solely based on
their linguistic scores had linguistics intelligence as their most dominant intelligence
while those who were placed in an undergraduate program solely based on their
mathematical scores had mathematical logical intelligence as their most dominant
intelligence. Based on these results, we can conclude that students whose most
dominant intelligence area is either linguistic or logical-mathematical intelligence were
guided to a related undergraduate program. In other words, the students who are
strong in those areas ended up having their multiple intelligence profiles match their
scores. However, participants’ intelligence profiles such as inter-personal, bodilykinesthetic, and naturalistic intelligences did not significantly differ with respect to their
three different types of exam scores obtained from the university entrance exam. It is
because the examination system itself is not designed to measure these intelligence
areas. That is said, the university entrance exam is not able to consider students’
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different abilities and skills derived from their higher mean levels of inter-personal,
bodily-kinesthetic, naturalistic, and musical intelligence areas while determining their
majors. For example, majors such as Visual Arts, Physical Education, Communication
Studies and Music Education require higher linguistics and combined scores. Therefore,
for instance, one would expect from students with highest mean level of inter-personal
intelligence to be placed into the Communication Studies based on their combined
scores since people with high inter-personal intelligence would have abilities and skills
required for different types of communication as indicated in the MI theory. However,
as seen above, students’ inter-personal intelligence did not differ with respect to their
combined scores. Likewise, we would expect students with highest mean level of
bodily-kinesthetic intelligence to be placed in the majors related to physical education
based on their combined scores. Similarly, Azar (2006) and Yalmanci’s (2011) also did
not report a significant difference between undergraduate students’ linguistic, musical,
bodily-kinesthetic, naturalistic and intrapersonal intelligence profiles with respect to
their majors while studying undergraduate students multiple intelligences difference by
majors.
It is also worth to note that students who want to get acceptance from majors
such as physical education or visual arts need to take extra exams organized by higher
education institutions in Turkey. These exams measure students’ abilities and skills in
these domains to determine their eligibility to enter these particular majors. Even
though it seems that the examination system attempts to measure different abilities and
skills, these types of exams only accounts for 30% of the total score. As seen, students’
scores from the entrance exam still remains as the main determinant and accounts for
the 70% of the total scores. Overall, the university entrance examination in Turkey tends
to place students whose linguistics and logical-mathematical intelligence domains are
strong. It is almost impossible for a student to enroll in a high-ranking university
without demonstrating strong ability in one of these intelligence areas.
Conclusion
Howard Gardner first presented MI theory over 25 years ago, which provides a
theoretical foundation for understanding individuals different abilities and capacities.
Further, the theory highlights that students may have an expertise in a diversity of areas
other than just having in linguistic and mathematical areas (McClellan & Conti, 2008).
The aim of this study was to establish that the university entrance examination system
for admissions into higher education in Turkey still continues to dismiss
recommendations proposed by recent developments in the field of education. Further,
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the MI scale used in this study helped researchers determine that there are statistically
significant differences between participants’ mean levels of multiple intelligence areas
by gender. Female and male participants had different types of intelligences as their
highest mean level of intelligences while students’ majors as determined by their
university entrance exam scores were only consistent with their linguistics and
mathematical intelligence areas.
Statistics related to the university entrance examination system in Turkey
portray a serious problem in the examination system such as not being inclusive
enough to involve different types of assessment which can determine participants’
different abilities and capacities. For instance, in an attempt to investigate students’
success in the university entrance exam in Turkey across the years, Berberoglu and
Kalender (2005) noted that students’ achievement level is very low in this examination
system and there is no sign of improvement across the years as is evidenced by the
success rate of below 50% at some public high schools in Turkey. Therefore, alternative
ways of placement into higher education institutions would benefit students who fails
in this examination system. Thus, students would have at least a chance to be assessed
in terms of their different abilities rather than being assessed based on only
mathematical and linguistic areas.
Acknowledgements
I would like to give my sincere thanks to David Trumpower and the anonymous
reviewers for their very helpful comments on earlier versions of this article.
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