The Gardner’s Multiple Intelligences and Academic Performance Among the Second-Semester Mechanical Engineering Students in
Politeknik Kuching Sarawak: A Correlation Analysis
Bong Nee Mel1*
1 Mechanical Engineering Department, Politeknik Kuching Sarawak, Sarawak, Malaysia
*Corresponding Author: [email protected] Accepted: 15 March 2021 | Published: 1 April 2021
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Abstract: The aim of this study is to determine which intelligences are strongest and most often used by the second semester of mechanical engineering students in Politeknik Kuching Sarawak. This study also investigates the relationship between the multiple intelligences and the students’ academic performance. In addition, the gender difference in multiple intelligences also have been examined. The interactive assessment of Multiple Intelligences for Adult Literacy and Education together with the separated items for existential intelligence were used in this study. The first-semester cumulative grade point average, CGPA of respondents was used as their academic achievement’s measurement. The analysis used in this study were descriptive statistics, independent sample t-test and Pearson product-moment correlation. The overall results found that the second semester of mechanical engineering students in Politeknik Kuching Sarawak preferred to use the mathematical-logical intelligence in their study and it followed by the intrapersonal intelligence and the bodily-kinesthetic intelligence. The results showed that the verbal-linguistic, visual-spatial, mathematical-logical, bodily-kinesthetic and musical intelligence had a positive correlation with the academic performance. The analysis also showed that the interpersonal, intrapersonal, naturalist and existential intelligence were negatively correlated with the academic performance. Meanwhile, there was no statistically significant difference found in the multiple intelligences due to gender difference. This survey may have provided the important and useful information for lecturers and Department of Mechanical Engineering to help students to discover their self-knowledges, talents, and abilities from the aspect of Gardner’s multiple intelligences in their learning and co-curricular activities, so that the students can perform well in their academic and non-academic parts during their study.
Keywords: multiple intelligences, academic performance, mechanical engineering
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1. Introduction
Dr. Howard Gardner, a professor of education at Harvard University had developed the theory of multiple intelligences in 1983 and introduced it through his book Frames of Mind: The Theory of Multiple Intelligences (Armstrong, n.d; Marenus, 2020; Cherry, 2019). According to Armstrong (n.d), the theory of multiple intelligences shows its important in school education and in adult learning and development. Therefore, the author had conducted the interactive assessment of Multiple Intelligences for Adult Literacy and Education (Shelton et. al., n.d) and the separated items for existential intelligence among the mechanical engineering students, semester 2 session of June 2020 in Politeknik Kuching Sarawak. The purpose of this survey
was to determine which intelligences are strongest and most often used by the respondents.
This study also investigates the relationship between the multiple intelligences and the students’ academic performance. In addition, the gender difference in multiple intelligences also have been examined.
2. Literature Review
There are nine intelligences proposed by Gardner that can be measured for instance the verbal- linguistic, mathematical-logical, visual-spatial, musical, bodily-kinesthetic, interpersonal, intrapersonal, naturalistic and existential intelligence (Minako Inoue, 2015; Nik Azlina and Sharifah Nina Shadzrina, 2020; Hajhashemi et. al. 2018; Jackson, 2011). The Gardner’s multiple intelligences had been summarized as below (Cortland, 2004; Nik Azlina and Sharifah Nina Shadzrina, 2020):
1) Verbal-Linguistic Intelligence (Word Smart): well-developed verbal skills and sensitivity to the sounds, meanings, and rhythms of words
2) Mathematical-Logical Intelligence (Logic / Number Smart): ability to think conceptually and abstractly, and capacity to discern logical and numerical patterns 3) Musical Intelligence (Music Smart): ability to produce and appreciate rhythm, pitch
and timber
4) Visual-Spatial Intelligence (Picture Smart): capacity to think in images and pictures, to visualize accurately and abstractly
5) Bodily-Kinesthetic Intelligence (Body Smart): ability to control one’s body movements and to handle objects skillfully
6) Interpersonal Intelligence (People Smart): capacity to detect and respond appropriately to the moods, motivations and desires of others
7) Intrapersonal Intelligence (Self Smart): capacity to be self-aware and in tune with inner feelings, values, beliefs and thinking processes
8) Naturalist Intelligence (Nature Smart): ability to recognize and categorize plants, animals and other objects in nature
9) Existential Intelligence (Life Smart): sensitivity and capacity to tackle deep questions about human existence, such as the meaning of life, why do we die, and how did we get here
There are numerous research studies relating to multiple intelligences and academic achievement. However, the author summarized only some here. According to Madkour and Mohamed (2016) in their study among the students at the College of Languages and Translation at Al-Imam Mohammad Ibn Saud Islamic University in Saudi Arabia, with the topic of student’s effective English language usages, they recommended that educators shall provide creative and effective teaching strategies by applying the multiple intelligences in higher education. The rational derived from their study was that the students managed to motivate and improve their language skills once they knew their multiple intelligences profiles. This research had contributed to teaching English for college students with the Gardner’s theory had been applied in the higher education. The significant findings from this research were a statistical relationship found between the multiple intelligences and the students’ motivation and language proficiency.
Salehi and Germai (2012) in their study among students at Sharif University of Technology, Iran by using the inventory of multiple intelligences found that most students possessed the
also stressed that the needs to foster other types of intelligences in the university study. This study results showed that the other intelligences (other than the logical-mathematical intelligence) were important too especially for the students’ achievements in other learning parts. According to the researchers, in the effort of producing the multi-dimensional students, then the students’ multiple intelligences and their talents or abilities must be discovered so much so that the students can cope with their academic and non-academic parts as well. The researchers concluded that although most engineering is endowed with the logical- mathematical intelligence but by applying the other intelligences as well will bring the students an extra advantage.
Hernandez et. al. (2019) in their research among the students aged between 8 and 16 years, San José de Cúcuta city, Colombia found that the logical-mathematical intelligence was the most dominant while the musical intelligence was the least dominant used among the respondents.
They also concluded there was no clear evident of association between the multiple intelligences and the grades in the school subjects. In addition, the researchers also revealed that age was not a significant parameter that related to the intelligences. Furthermore, they also found that the school performance for female students was significantly higher than male students. Meanwhile, the female students were stronger in naturalistic intelligence while the males showed slightly more potential in the visual-spatial and bodily-kinesthetic intelligence.
Ahvan and Pour (2016) presented that the high school students of Bandar Abbas, Iran most dominant with the verbal-linguistic intelligence while the musical intelligence was the students’ least dominant intelligence. They also found that multiple intelligences were interconnected and supported to each other. Besides, they also revealed that the verbal- linguistic and the visual-spatial intelligence were correlated moderately with the academic achievement. In addition, the interpersonal, intrapersonal, naturalistic, and bodily-kinesthetic intelligences were weakly correlated while the musical intelligence was not correlated to the academic achievement. According to the researchers again, by identifying and implementing the multiple intelligences on the high school students by their teachers in teaching and learning process may aware the self-knowledges and abilities of the students in enhancing their academic performance. In another research by Ahvan et. al. (2016) regarding the correlation between Gardner's multiple intelligences and problem-solving styles and their role in the academic performance of high school students of Bandar Abbas, Iran, they revealed that the verbal-linguistic, bodily-kinesthetic, logical-mathematical and musical intelligence were significant positively and moderately correlated with the academic achievement. This study also showed the statistically significant effect of problem-solving styles on the academic achievement. Thus, the researchers suggested that the multiple intelligences and the problem- solving styles need to be cultivated together in teaching and learning process.
Kandeel (2016) studied the pattern of the multiple intelligences among 917 students at King Saud University, Saudi Arabia, and its relationship with the academic achievement for mathematics. The study showed the pattern of multiple intelligences of the respondents was in the following order: self, social, bodily, logical, verbal, visual, musical and natural intelligence.
Besides, the study also illustrated the impact of multiple intelligences (visual, bodily, logical, and sometimes social, musical, and natural) on mathematics achievement. Therefore, the researcher recommended that the teachers must employ the multiple intelligences among their students and encourage them to cultivate it in their learning process for better academic performance. Furthermore, teachers needed the educational training to master the theory of multiple intelligences and its implementation in the educational practices so much so that the
teachers could use the right educational approaches and strategies that paralleled with the multiple intelligences in their students’ learning.
Aydin (2019) conducted a research to determine the positive influence of the creation and implementation of multiple intelligences-based learning and teaching activities to the students’
academic success. The research was conducted on secondary / middle school in the Central Anatolian Region. The findings showed that the multiple intelligences-based learning and teaching techniques were seen to influence positively on the student’s success. The students exposed to such techniques and activities were found to be more successful than the students with traditional methods employed. Besides, the students had undergone the multiple intelligences’ application in learning showed more positive attitudes for learning than those students who had not participated it.
Emendu and Udogu (2013) carried out a quasi-experimental research work to examine the efficacy of multiple-intelligence teaching strategies in enhancing chemistry students’
achievement. Two co-educational secondary schools were selected from the urban area of Onitsha educational zone: one school served as the experimental group with multiple- intelligence teaching strategy implemented while the other one served as the control group with only conventional instructional method employed. The findings showed that the properly implementation of multiple-intelligence teaching strategy could enhance students’
achievements. Thus, the researchers concluded that the teachers should be trained for integrating and applying the multiple-intelligence teaching strategies to develop and enhance the students’ potentials in learning process.
According to Ikiz and Cakar (2010) in their study of the relation between the multiple intelligences and the academic achievement for 250 secondary school students in Izmir, Turkey concluded that the academic achievement scores were found to be dependent on the student’s multiple intelligences. They found that the student who had lower academic achievement level with usually directly proportional to the student lower verbal-linguistic, logical-mathematical, interpersonal, and intrapersonal ability then the others. Besides, this study also found that the dominant multiple intelligences differed in students due to the gender difference. They also discovered the encouraging relation between the musical intelligence and the academic achievement scores in this study.
Habibollah Naderi et. al. (2010) had conducted their research to examine the relationship between the intelligences and the academic achievement as well as its relationship due to the gender difference. The analysis indicated that the aspects of intelligence were not significantly related to the academic achievement for both genders.
3. Methodology
This study was a descriptive survey. The respondents were drawn from the Mechanical Engineering students of semester 2 session of June 2020 in Politeknik Kuching Sarawak. The interactive assessment of Multiple Intelligences for Adult Literacy and Education (Shelton et al., n.d) and the separated items for existential intelligence were used to gather information related to the objectives of the study. In addition, the first-semester cumulative grade point average, CGPA of respondents was used as their academic achievement’s measurement. This survey was conducted online due to the pandemic COVID-19. The analysis used in this study were descriptive statistics, independent sample t-test and Pearson product-moment correlation.
(a) to explore the type of intelligences which are strongest and most often used by the respondents.
(b) to examine any differences in the multiple intelligences due to gender difference.
(c) to investigate the relationship between the multiple intelligences and the students’
academic performance.
4. Discussion and Conclusion
There were 67 engineering students of semester 2 session of June 2020 in Mechanical Engineering Department answered this survey. Figure 1 shows the demographic data of the respondents in this survey. There were 69 % of male students and 31% of female students.
Meanwhile, according to the mechanical engineering programs offered, there were 61% of DKM (Diploma in Mechanical Engineering) students, almost a quarter of number of DAD (Diploma in Mechanical Engineering – Automotive) students, only 10% of DTP (Diploma in Mechanical Engineering – Manufacturing) students and a very small portion of DPU (Diploma in Mechanical Engineering – Air Conditioning & Refrigeration) students.
(a) (b)
Figure 1: Distribution of respondents of semester 2 mechanical engineering students:
(a) according to gender; (b) according to engineering programs offered.
Table 1 shows the descriptive statistics of respondents according to the 9 Gardner’s multiple intelligences. It was found that students were stronger and most often used the mathematical- logical intelligence (M=3.7924) and it followed by the intrapersonal intelligence (M=3.6433) and the bodily-kinesthetic intelligence (M=3.5872). The less dominant intelligence used by the respondents was existential intelligence (M=3.1531). The mathematical-logical intelligence or the logic / number smart was highly developed among the mechanical engineering students due to the needs of this ability in solving engineering problems, engineering calculations and logical thinking as well. This finding was paralleled to Salehi and Germai (2012) since this intelligence was highly relevant to the engineering fields. Thus, the mathematical-logical intelligence was the important core to the engineering.
The second highly developed intelligence among the respondents was the intrapersonal intelligence might be due to most of them were introverted or possessed the self-reflection or self-examination ability. The thirdly high-mean intelligence was the bodily-kinesthetic intelligence since the engineering students frequently worked with their hands-on projects by producing, investigating, testing, or experimenting.
Although the other intelligences for instance the verbal-linguistic, interpersonal, visual-spatial and so on found to be moderately or less dominant among the respondents in this survey, but they still been very important too especially in some situations or work tasks. The visual-spatial intelligence, for example might be important for the engineering students to visualize and understand the interaction of aspects in a design. The interpersonal and the verbal-linguistic intelligences too might be important for the engineering students to communicate and team up for better knowledge sharing, brainstorming and new technology invention. Therefore, the educators should play an important role to motivate students to discover and employ their multiple intelligences in the engineering studies and in their later profession as stressed by Salehi and Germai (2012).
Table 1: Descriptive statistics of respondents according to the Gardner’s multiple intelligences.
Mean Std. Deviation N Mathematical-Logical (Logic / Number Smart) 3.7924 0.46035 67
Intrapersonal (Self Smart) 3.6433 0.61116 67
Bodily-Kinesthetic (Body Smart) 3.5872 0.51044 67
Verbal-Linguistic (Word Smart) 3.5587 0.51794 67
Interpersonal (People Smart) 3.5182 0.61008 67
Visual-Spatial (Picture Smart) 3.4569 0.59363 67
Musical (Music Smart) 3.2737 0.75756 67
Naturalist (Nature Smart) 3.2557 0.41938 67
Existential (Life Smart) 3.1531 0.30701 67
CGPA 3.5524 0.32313 67
Table 2: Gardner’s multiple intelligences according to gender, independent samples t-test.
Gender N Mean Std.
Deviation
t P Value Verbal-Linguistic
(Word Smart)
Male 46 3.4809 0.51208 -1.853 0.068
Female 21 3.7290 0.50085
Mathematical- Logical (Logic / Number Smart)
Male 46 3.6961 0.53444 0.121 0.904
Female 21 3.6795 0.47957
Musical (Music Smart)
Male 46 3.2524 0.73030 -0.339 0.736
Female 21 3.3205 0.83097
Visual-Spatial (Picture Smart)
Male 46 3.5061 0.60520 1.005 0.319
Female 21 3.3490 0.56661
Bodily-Kinesthetic (Body Smart)
Male 46 3.5946 0.51952 0.174 0.862
Female 21 3.5710 0.50212
Interpersonal (People Smart)
Male 46 3.5437 0.60973 0.503 0.617
Female 21 3.4624 0.62208
Intrapersonal (Self Smart)
Male 46 3.5983 0.62951 -0.891 0.376
Female 21 3.7419 0.57106
Naturalist (Nature Smart)
Male 46 3.5680 0.54581 0.022 0.983
Female 21 3.5648 0.62654
Existential (Life Smart)
Male 46 3.1637 0.31457 0.414 0.680
Female 21 3.1300 0.29596
An independent-samples t-test was conducted to compare the Gardner’s multiple intelligences according to the gender as displayed in Table 2. The findings showed that the difference between the male and the female students in all the multiple intelligences were statistically insignificant. For example, there was an insignificant difference in the scores for the verbal- linguistic intelligence for male (M=3.4809, SD=0.51208) and female (M=3.729, SD=0.50085) with t (65) = -1.853, p = 0.068. Besides, there was an insignificant difference in the scores for the mathematical-logical intelligence for male (M=3.6961, SD=0.53444) and female
(M=3.6795, SD=0.47957) with t (65) = 0.121, p = 0.904. For other intelligences such as the musical, the visual-spatial, the bodily-kinesthetic, the interpersonal, the intrapersonal, the naturalist and the existential intelligence with both genders were statistically insignificant because the t-values were (0.339), (1.005), (0.174), (0.503), (0.891), (0.022) and (0.414) respectively. In overall, these results showed that there was no statistically significant difference between the male and the female students regarding the Gardner’s multiple intelligences in their engineering study.
From Table 2 again, the male and female students showed the different multiple intelligences they most often used. The male students were more dominant in the mathematical-logical intelligence (M = 3.6961) and followed by the intrapersonal intelligence (M = 3.5983) and the bodily-kinesthetic intelligence (M = 3.5946). Meanwhile, the female students were more dominant in the intrapersonal intelligence (M = 3.7419) and followed by the verbal-linguistic intelligence (M = 3.729) and the mathematical-logical intelligence (M = 3.6795). This result was paralleled to the findings of Ikiz and Cakar (2010) that the dominant multiple intelligences differed in students due to the gender difference.
Table 3 shows the correlation between Gardner’s multiple intelligences and the student academic performance. As can be seen, the correlations of the five intelligences with the CGPA of the students were positive but low, such as the verbal-linguistic intelligence / word smart (r
= 0.066), the mathematical-logical intelligence / logic-number smart (r = 0.1), the musical intelligence / music smart (r = 0.036), the visual-spatial intelligence / picture smart (r = 0.13) and the bodily-kinesthetic intelligence / body smart (r = 0.022). From these five positive correlations, the top three highest belonged to the visual-spatial intelligence, the mathematical- logical intelligence and the verbal-linguistic intelligence which they seem like more related to the engineering field. The positive correlation meant that the more often the students used those intelligences in their studies, the higher and better their academic performance or achievement would be. This was paralleled with Ahvan et. al. (2016), Kandeel (2016), Hernandez et. al.
(2019), Aydin (2019), Emendu and Udogu (2013), Madkour and Mohamed (2016), Ahvan and Pour (2016) and Ikiz and Cakar (2010) in their study with conclusion that the statistical positive relationship (but weak to moderate) was found between the academically related multiple intelligences and the students’ motivation and academic performance. Therefore, educators are to be encouraged to employ the multiple intelligences in teaching and learning process among their students since the above intelligences were positively correlated with the academic performance.
On the other hand, the remaining four intelligences as shown in Table 3 were low and negatively correlated with the students’ CGPA for instance the interpersonal intelligence / people smart (r = -0.135), the intrapersonal intelligence / self-smart (r = -0.078), the naturalist intelligence / nature smart (r = -0.117) and the existential intelligence / life smart (r = -0.047).
These four intelligences were negatively correlated with academic result of CGPA might be due to the irrelevant or unrelated of such intelligences to student’s academic studies. This finding was paralleled to the study, for examples of Ahvan and Pour (2016) and Kandeel (2016), that some intelligences were weakly or even not so correlated to the academic achievement. However, Salehi and Germai (2012) still pointed that the needs to foster other not-so-academically-related types of intelligences in education to produce the multi- dimensional students.
Table 3: Correlation between Gardner’s multiple intelligences and student academic performance, N=67.
Word Smart
Logic / Number
Smart
Music Smart
Picture Smart
Body Smart
People Smart
Self Smart
Nature Smart
Life Smart
CGPA
Word Smart
Pearson r
1 .199 .116 .463** .169 .265* .029 -.050 -.213 .066
Sig. (2- tailed)
.107 .348 .000 .171 .030 .816 .688 .084 .595
Logic / Number
Smart
Pearson r
.199 1 -.210 .378** .018 -.047 -.102 -.013 .127 .100
Sig. (2- tailed)
.107 .088 .002 .886 .704 .411 .919 .304 .419
Music Smart
Pearson r
.116 -.210 1 .216 .358** .379** .468** .013 .030 .036
Sig. (2- tailed)
.348 .088 .079 .003 .002 .000 .918 .809 .775
Picture Smart
Pearson r
.463** .378** .216 1 .330** .208 .183 .079 -.038 .130
Sig. (2- tailed)
.000 .002 .079 .006 .091 .138 .524 .757 .296
Body Smart
Pearson r
.169 .018 .358** .330** 1 .502** .378** -.133 .070 .022 Sig. (2-
tailed)
.171 .886 .003 .006 .000 .002 .285 .572 .857
People Smart
Pearson r
.265* -.047 .379** .208 .502** 1 .371** -.135 -.032 -.135 Sig. (2-
tailed)
.030 .704 .002 .091 .000 .002 .278 .795 .274
Self Smart
Pearson r
.029 -.102 .468** .183 .378** .371** 1 .058 -.009 -.078 Sig. (2-
tailed)
.816 .411 .000 .138 .002 .002 .642 .942 .531
Nature Smart
Pearson r
-.050 -.013 .013 .079 -.133 -.135 .058 1 .120 -.117
Sig. (2- tailed)
.688 .919 .918 .524 .285 .278 .642 .333 .347
Life Smart
Pearson r
-.213 .127 .030 -.038 .070 -.032 -.009 .120 1 -.047
Sig. (2- tailed)
.084 .304 .809 .757 .572 .795 .942 .333 .704
CGPA Pearson r
.066 .100 .036 .130 .022 -.135 -.078 -.117 -.047 1
Sig. (2- tailed)
.595 .419 .775 .296 .857 .274 .531 .347 .704
Note: Correlation with (**) is significant at the 0.01 level (2-tailed).
Correlation with (*) is significant at the 0.05 level (2-tailed).
In terms of intercorrelations of the intelligence types, some intelligences really showed the relatively higher correlation indices. For example, the musical intelligence with the intrapersonal intelligence showed the highest intercorrelation of r = 0.468, significant at the 0.01 level. The lowest intercorrelation was found on the existential intelligence with the intrapersonal intelligence with r = -0.009. From Table 3, in overall, most of the multiple intelligences were found to be better intercorrelated and this result supported by the study of Ahvan and Pour (2016).
As a conclusion, the overall survey results found that the mechanical engineering students of
mathematical-logical intelligence and it followed by the intrapersonal intelligence and the bodily-kinesthetic intelligence since these intelligences were highly relevant to the engineering study. Besides, the findings also showed that the difference between the male and the female students in all the multiple intelligences were statistically insignificant. The male students were more dominant in the mathematical-logical intelligence while the female students were more dominant in the intrapersonal intelligence. Finally, the positive but low correlations were found between the verbal-linguistic, mathematical-logical, musical, visual-spatial and bodily- kinesthetic intelligences with the academic performance. Meanwhile, the negative and low correlations were found between the interpersonal, intrapersonal, naturalist and existential intelligences with the academic performance. Some of the intelligence types showed higher intercorrelations indices with the others.
This survey may have provided the important and useful information for lecturers and Department of Mechanical Engineering to help students to discover their self-knowledges, talents, and abilities from the aspect and theory of Gardner’s multiple intelligences in their learning and co-curricular activities, so that the students can cope with their academic and non- academic performance in their study.
Furthermore, it is suggested that this study can be extended by favourable to enlarge its scope to determine the Gardner’s multiple intelligences profiles and their relationships to the academic performance for the non-engineering students in future studies. A longitudinal study may also carry out to observe the developments or changes in the students’ multiple intelligences over a period of times and its relations to the academic performance.
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