Content uploaded by Veljko Aleksić
Author content
All content in this area was uploaded by Veljko Aleksić on Jul 26, 2018
Content may be subject to copyright.
Digital Gameplay Habits and Multiple Intelligences Profile of Early Adolescents
Living in Rural Areas
Veljko Aleksiü
University of Kragujevac
Faculty of Technical Sciences
ýaþak, Serbia
e-mail: veljko.aleksic@ftn.kg.ac.rs
Mirjana Ivanoviü
University of Novi Sad
Faculty of Sciences
Novi Sad, Serbia
e-mail: mira@dmi.uns.ac.rs
Abstract—The purpose of the research is to provide an
empirical insight into the gameplay preferences and multiple
intelligences profile of early adolescents living in rural areas. It
was found that the early adolescent males living in rural areas
played digital games about two times more than females did,
and that the average weekly gameplay time increased as
students grew. Females achieved significantly higher levels of
Bodily/kinesthetic intelligence than males did. Gender and age
can be observed as predictors of average daily gameplay time.
The levels of Visual/spatial, Verbal/linguistic, Interpersonal
and Natural intelligence can be observed as the predictors of
average weekly gameplay time. Socio-cultural influence of the
living environment presented a significant factor for digital
gameplay habits and multiple intelligence profile of early
adolescents.
Keywords-early adolescents; digital games; multiple
intelligences; rural area
I.
I
NTRODUCTION
Digital games have become an indispensable part of the
early adolescent lives and youth culture, both in urban and
rural socio-cultural environments. The living and educational
environments are nowadays crowded with (often
interconnected) digital devices such as PC’s, smartphones,
tablets, gaming consoles etc., so digital games can be played
anywhere and anytime. As such, their influence on the lives
of children and adolescents that are educating (and those that
soon will) cannot be allowed to be overlooked nor
marginalized. The student cognitive, affective and
psychomotor characteristics are surely affected by the
contemporary multi-sensuous extensive digital games, thus
activating various intelligence modalities [1]. Experts often
define the intelligence as the total capacity for learning and
problem solving [2], so researchers in education are natively
interested in its measurement in order to determine how the
students can gain the most of the educational process.
Numerous researchers examined the factor structure of
intelligence, ranging from Thurstone [3]. Since the end of the
twentieth century, the group of psychologists started to
actively develop, explore and expand the theory of multiple
intelligences in accordance to the belief that the specific
individual advantages and disadvantages can be expressed
through the possession of multiple skills [4]. In this case, the
intelligence is defined as the personal ability to successfully
meet the new situational demand and the capacity to learn
from previous experience [5]. The theory of multiple
intelligences is based on evolutionary biology, neuroscience,
psychometrics and psychological research [6].
The rest of the paper is organized as follows. Section 2
focuses on the short review of educational significance of
digital games and multiple intelligences. In Section 3, we
presented the overview of research methodology, following
the results of rural early adolescent digital gameplay habits
and multiple intelligences profile in Section 4. The last
section gives concluding remarks on the topic.
II. R
ELATED
W
ORK
The promotion of commercial off-the-shelf digital games
educational potential intensified in the last couple of decades
as digital technologies and internet access became ubiquitous
which consequently wider the field of their implementation.
Game-based learning gradually and inexorably integrates
into teaching practice mainly as the mean for bridging the
gap between traditionally low-tech formal learning
environment in rural areas and the “digital” generation of
students on the other [7]. Gaming obviously became a part of
the youth culture in rural areas also, which consequently
directly influences the multiple intelligences profile of early
adolescents, as culture plays an important role in the
development of intelligences [8]. The theory of multiple
intelligences attracted attention because it is not concerned
with psychometric precise definition of intellectual ability,
but describes the recognizable behavior or directly
observable manifestations and enables self-assessment. The
adaptation of teaching methodology in accordance to the
theory of multiple intelligences can lead to efficient use of
student personal aspirations aimed at development of
positive motivation, achievement improvement and
competencies empowerment.
The extensive literature review of empirical research on
effects of digital games on multiple intelligences [1] resulted
in relatively small number of papers that analyzed the
influence of commercial off-the-shelf games on learning or
personality. The effects of digital games on spatial
intelligence was researched by quasi-experiments on the
sample of 40 high school students [9], and the correlation
between spatial intelligence and complementary educational
images was identified. The influence of digital gameplay was
observed on teenage expert video game players aged 10-11
[10], and it was concluded that advanced players
demonstrated better assessment of the unknown situations,
2017 IEEE 17th International Conference on Advanced Learning Technologies
2161-377X/17 $31.00 © 2017 IEEE
DOI 10.1109/ICALT.2017.35
119
information categorization and critical thinking skills. A
group of researchers developed personally designed
pictograms through which the children could associate
grammatical structures with their ideas in order to increase
the interaction and social communication in the context of
special education [11], and concluded that playing digital
games helped achieving better spatial coordination,
concentration and motivation. MathMazing digital game was
applied in teaching elementary school arithmetic by the
group of researchers [12], which concluded that the effective
and practical teaching was realized, thus leading to the
improvement of learning retention. The effects of
educational games on the strategies of multiple intelligences
development and the enhancement of logical/mathematical
intelligence level were also analyzed and elaborated [13].
The observation on the reviewed papers is that playing
digital games generally leads to the improvement of
students’ cognitive abilities and skills.
It should be noted that some researchers [14] [15] failed
to establish the correlation between the frequency and time
spent playing commercial off-the-shelf games and the
average grades or school achievement.
III. R
ESEARCH
M
ETHODOLOGY
The research problem is how living in rural environment
affects digital gameplay habits and multiple intelligences
profile of early adolescents (higher grades elementary school
students). The main objective of the research is the self-
assessment of digital gameplay preferences, habits and
multiple intelligences profile of early adolescents in rural
areas.
The research was conducted in eight rural Serbian
elementary schools in 2015. The study included 461 students
aged 11-15, out of which 232 (50.3%) were male and 229
(49.7%) were female. The average age of the examinees was
12.9 years (SD = 1.19). Schools were selected to equally
represent various geographical, economic and socio-cultural
milieu.
Multiple intelligences profile was assessed using
psychometrically evaluated IPVIS-OS instrument [16].
Students anonymously, voluntary and independently filled
the questionnaire in paper-pencil form in the school
premises.
IV. R
ESULTS
The average weekly gameplay time of (N = 408; 88.5%)
students that play games and live in rural areas was 13.8
hours (SD = 13.9). An independent samples t-test was
conducted to examine whether there was a significant gender
difference between early adolescents in relation to the
average weekly gameplay time. The test revealed a
statistically significant difference between male and female
early adolescents living in rural areas (t = 6.86, df = 400.7, p
< 0.001). Males (M = 17.8, SD = 14.8) reported significantly
higher average weekly gameplay time than did females (M =
9.06, SD = 11.0).
The average daily gameplay time of early adolescents
that live in rural areas was 149.6 minutes (SD = 108.8). The
t-test revealed a statistically significant difference between
male and female early adolescents in daily gameplay time (t
= 7.62, df = 405.1, p < 0.001). Males (M = 184.2, SD =
111.8) reported significantly higher average daily gameplay
time than did females (M = 89.3, SD = 89.3).
Rural early adolescents most often played digital games
regardless of the time of the day (N = 117; 25.4%). There
were no statistically significant differences by the gender in
relation to the time of the day that students played digital
games (t = 4.21, df = 409, p < 0.001).
Most of the students played digital games for longer than
five years (N = 185; 40.1%). There were statistically
significant differences by the gender in relation to the length
of the period that students played digital games (t = 3.07, df
= 287.3, p = 0.002). Male early adolescents reported
significantly longer period of playing digital games than did
females (p < 0.001).
Students mainly played digital games on their home
computers/laptops (N = 241; 52.3%) and smartphones (N =
151; 32.8%). There were statistically significant differences
by the gender in relation to the preferred devices that
students played digital games on (t = -6.32, df = 429.8, p <
0.001). Female early adolescents significantly more preferred
playing digital games on their smartphones than on home
computers/laptops (p < 0.001).
There were statistically significant differences by the
gender of early adolescents in relation to playing digital
games socially (t = 5.09, df = 447.0, p < 0.001). Male early
adolescents significantly more (p < 0.001) preferred playing
digital games socially than females did.
There were no statistically significant differences by the
gender in relation to playing digital games online (t = 0.28,
df = 455, p = 0.779).
The most often preferred digital game genres of early
adolescents living in rural areas were Action games (N = 93;
20.2%), Sports games (N = 80; 17.4%) and Logical games
(N = 80; 17.4%).
The ANOVA analysis resulted that there were significant
differences in the average weekly gameplay time by the early
adolescent age [F
(4, 403)
= 3.53; p = 0.008; Ș
2
= 0.034]. Tukey
post-hoc test show that 11-year-old early adolescents spent
statistically significantly less time on weekly average playing
digital games compared to 14-year-olds (p = 0.009), and that
12-year-old students also spent statistically significantly less
weekly time playing games that 14-year-olds did (p = 0.032).
The correlation analysis results show that the average
school grade was not significantly correlated to the average
weekly gameplay time. However, the average school grade
significantly negatively weakly correlated with the average
daily gameplay time (r
s
(408)
= -0.098; p = 0.048). The
increase of the amount of daily time spent playing decreases
the average school grade of early adolescents living in rural
areas.
There were statistically significant differences on average
intelligence level by the gender of early adolescents living in
rural areas for Bodily/kinesthetic intelligence (t = -0.20, df =
448.9, p = 0.002). There were no statistically significant
differences on average intelligence levels by the gender for
Musical/rhythmic (t = -9.32, df = 459, p = 0.768),
Logical/mathematic (t = 0.83, df = 459, p = 0.091),
120
Visual/spatial (t = -8.59, df = 459, p = 0.253),
Verbal/linguistic (t = -5.68, df = 459, p = 0.966),
Interpersonal (t = -2.11, df = 459, p = 0.958), Intrapersonal (t
= -0.74, df = 459, p = 0.979) and Natural (t = -1.35, df = 459,
p = 0.771) intelligence. Table 1 presents the overview of the
average self-assessed levels of intelligences of early
adolescents living in rural areas.
TABLE I. T
HE
A
VERAGE
L
EVELS
O
F
I
NTELLIGENCES
Intelligence
M SD
Musical/rhythmic
61.0 16.0
Bodily/kinesthetic 64.2 16.0
Logical/mathematic 68.5 15.8
Visual/spatial 63.2 16.5
Verbal/linguistic 65.8 14.6
Interpersonal 70.2 15.0
Intrapersonal 69.3 15.0
Natural 67.6 16.0
Point-Biserial correlation analysis show that early
adolescent gender significantly positively correlated with the
average levels of Musical/rhythmic (r
pb (461)
= 0.40; p <
0.001), Visual/spatial (r
pb (461)
= 0.37; p < 0.001) and
Interpersonal (r
pb (461)
= 0.098; p = 0.035) intelligence.
Spearman correlation analysis results show that the
average school grade significantly correlated to the average
levels of Musical/rhythmic (r
s
(461)
= 0.15; p = 0.001),
Bodily/kinesthetic (r
s
(461)
= 0.14; p = 0.002),
Logical/mathematic (r
s
(461)
= 0.48; p < 0.001), Visual/spatial
(r
s
(461)
= 0.16; p < 0.001), Verbal/linguistic (r
s
(461)
= 0.34; p
< 0.001), Interpersonal (r
s
(461)
= 0.22; p < 0.001) and
Intrapersonal (r
s
(461)
= 0.18; p < 0.001) intelligence.
There were statistically significant positive correlations
between the average weekly gameplay time and the average
levels of Bodily/kinesthetic (r
s
(408)
= 0.11; p = 0.032),
Interpersonal (r
s
(408)
= 0.19; p < 0.001) and Intrapersonal (r
s
(408)
= 0.16; p = 0.001) intelligence.
There were statistically significant positive correlations
between the average daily gameplay time and the average
levels of Interpersonal (r
s
(408)
= 0.14; p = 0.004) and
Intrapersonal (r
s
(408)
= 0.12; p = 0.018) intelligences. There
also was a statistically significant negative correlation
between the average daily gameplay time and the average
level of Visual/spatial intelligence (r
s
(408)
= -0.12; p =
0.013).
A multiple linear regression was calculated to predict
daily gameplay time based on early adolescents age and
gender. A significant regression equation was found [F
(2, 405)
= 30.9, p < 0.001], with an R
2
of 0.133. Result analysis show
that gender [ȕ = -0.34; t
(405)
= -7.24; p < 0.001] and age [ȕ =
0.11; t
(405)
= 2.33; p = 0.020] significantly predicted average
daily gameplay time which increased by 9.79 minutes per
every year of age, and early adolescent males played on
average 73.5 minutes daily [95% CI (53.5 – 93.5)] more than
females.
A multiple linear regression was also calculated to
predict weekly gameplay time based on the levels of early
adolescent intelligences. A significant regression equation
was found [F
(8, 396)
= 6.21, p < 0.001], with an R
2
of 0.111.
Result analysis show that Visual/spatial [ȕ = -0.16; t
(396)
= -
2.30; p = 0.022], Verbal/linguistic [ȕ = -0.23; t
(396)
= -3.00; p
= 0.003], Interpersonal [ȕ = 0.26; t
(396)
= 3.29; p = 0.001]
and Natural [ȕ = -0.16; t
(396)
= -2.62; p = 0.009] intelligences
significantly predicted average weekly gameplay time which
decreased by 0.13 hours per 10% increase of level of
Visual/spatial intelligence [95% CI (0.02 – 0.25)], by 0.22
hours per 10% increase of level of Verbal/linguistic
intelligence [95% CI (0.08 – 0.37)] and 0.14 hours per 10%
increase of level of Natural intelligence [95% CI (0.04 –
0.25)], while increased by 0.24 hours per 10% increase of
level of Interpersonal intelligence [95% CI (0.10 – 0.39)].
V. C
ONCLUDING
R
EMARKS
The results showed that early adolescent males living in
rural areas played digital games significantly more than
females did, roughly about two times on weekly/daily
average. Males also reported playing games for significantly
longer period of time than females did. Females more
preferred playing games on their smartphones, but less
preferred playing games socially. About 55% of questioned
early adolescents preferred Action, Sports and Logical
games in total. As students grew, they increased the average
weekly gameplay time. Interestingly, the increase of daily
gameplay time led to drop of average school grade of early
adolescents living in rural areas.
Only significant gender difference of early adolescent
intelligences was recorded in Bodily/kinesthetic levels,
where females achieved higher levels than males did. The
average weekly gameplay time increased with the increase of
levels of Bodily/kinesthetic, Interpersonal and Intrapersonal
intelligences.
Gender and age of early adolescents living in rural areas
can be observed as predictors of average daily gameplay
time, as it increased by every year of age and males played
digital games 73.5 minutes more than females did. Assessed
levels of Visual/spatial, Verbal/linguistic, Interpersonal and
Natural intelligence can also be observed as predictors of the
average weekly gameplay time.
The integration of digital games in formal and informal
educational environment and their adequate selection in
accordance to the student multiple intelligences profile
provides the mean for intuitive acquisition of knowledge and
skills in relatively controlled environment. Besides that, the
development of competences should not be burdened by the
traditional teaching methods, as students can be given the
opportunity to spend much more time learning, exploring
and training through playing games. Contemporary digital
technologies can provide the sense of fun in many ways, by
which they become an incubator of innovative and informal
media for transferring knowledge, and gaining problem
solving or critical thinking skills. In addition, the theory of
multiple intelligences has the potential to change the role of
teachers, from explaining the learning content to a moderator
or learning guide.
121
Socio-cultural influence of the living environment is a
significant factor for digital gameplay habits and multiple
intelligence profile of early adolescents. Social effects of
playing digital games can also be demonstrated on the
examples of new grouping forms and player communication
and organization.
R
EFERENCES
[1] V. Aleksiü and M. Ivanoviü, “A Literature Review of Empirical
Research on Effects of Digital Games on Learning Styles and
Multiple Intelligences,” Croatian Journal of Education, in press.
[2] R. J. Sternberg, “Patterns of giftedness: A triarchic analysis,” Roeper
Review, vol. 22, no. 4, Jun. 2000, pp. 231–235, doi:
10.1080/02783190009554044.
[3] L. L. Thurstone, “The factorial isolation of primary abilities,”
Psychometrika, vol. 1, no. 3, Sep. 1936, pp. 175–182,
doi:10.1007/bf02288363.
[4] D. W. Chan, “Perceived Multiple Intelligences Among Male and
Female Chinese Gifted Students in Hong Kong: The Structure of the
Student Multiple Intelligences Profile,” Gifted Child Quarterly, vol.
50, no. 4, Oct. 2006, pp. 325–338,
doi:10.1177/001698620605000405.
[5] H. Gardner, “Multiple intelligences: the theory in practice,” Choice
Reviews Online, vol. 31, no. 02, Oct. 1993, pp. 31–1214–31–1214,
doi:10.5860/choice.31-1214.
[6] V. Aleksiü and M. Ivanoviü, “Early Adolescent Gender and Multiple
Intelligences Profile as a Predictors of Digital Gameplay
Preferences,” Croatian Journal of Education, in press.
[7] V. Aleksiü and M. Ivanoviü, “Can Digital Game-Based Learning be
incorporated in Serbian Primary School Curricula's?” Proc. 7th
Balkan Conference on Informatics – BCI ’15, ACM, 2015, pp. 38:1-
38:7, doi:10.1145/2801081.2801090.
[8] J. Q. Chen, S. Moran, and H. Gardner, Multiple intelligences around
the world, John Wiley & Sons, 2009.
[9] F. Malekian, A. R. F. Pour, and B. S. Pour, “Study the Effect of
Supplemental Instructional Images on Students’ Spatial Intelligence
Degree,” Procedia - Social and Behavioral Sciences, vol. 46, 2012,
pp. 3301–3305, doi:10.1016/j.sbspro.2012.06.055.
[10] S. S. VanDeventer and J. A. White, “Expert behavior in children’s
video game play,” Simulation & Gaming, vol. 33, no. 1, 2002, pp. 28-
48, doi:10.1177/1046878102033001002.
[11] J. L. González, M. J. Cabrera, and F. L. Gutiérrez, “Using
Videogames in Special Education,” Computer Aided Systems
Theory–EUROCAST 2007, 2007, pp. 360–367, doi:10.1007/978-3-
540-75867-9_46.
[12] N. Gosalia, P. Jain, I. Shah, A. R. Joshi, N. Katre, and S.
Sahasrabudhe, “3D Gesture-recognition Based Animation Game,”
Procedia Computer Science, vol. 45, 2015, pp. 712–717,
doi:10.1016/j.procs.2015.03.138.
[13] J. Li, S. Ma, and L. Ma, “The Study on the Effect of Educational
Games for the Development of Students’ Logic-Mathematics of
Multiple Intelligence,” Physics Procedia, vol. 33, 2012, pp. 1749–
1752, doi:10.1016/j.phpro.2012.05.280.
[14] E. Wack and S. Tantleff-Dunn, “Relationships between Electronic
Game Play, Obesity, and Psychosocial Functioning in Young Men,”
CyberPsychology & Behavior, vol. 12, no. 2, Apr. 2009, pp. 241–
244, doi:10.1089/cpb.2008.0151.
[15] A. Drummond and J. D. Sauer, “Video-Games Do Not Negatively
Impact Adolescent Academic Performance in Science, Mathematics
or Reading,” PLoS ONE, vol. 9, no. 4, Apr. 2014, p. e87943,
doi:10.1371/journal.pone.0087943.
[16] V. Aleksiü and M. Ivanoviü, “Psychometric evaluation of the
reliability of IPVIS-OS multiple intelligences assessment instrument
for early adolescents,” Journal of Educational Sciences and
Psychology, vol. VI(LXVIII), no. 1, 2016, pp. 21-34.
122
