· Web viewTHE CORRELATION BETWEEN BRAIN HEMISPHERIC DOMINANCE AND LEARNERS’ ENGLISH SPEAKING PERFORMANCE Abdul Hakim Yassi1 and Umar2 1Cultural Science Faculty of Hasanuddin University

THE CORRELATION BETWEEN BRAIN HEMISPHERIC DOMINANCE AND LEARNERS’ ENGLISH SPEAKING PERFORMANCE

Abdul Hakim Yassi1 and Umar2

1Cultural Science Faculty of Hasanuddin University of Makassar, [email protected]

2Faculty of Letters of Satria University of Makassar, [email protected]

Abstract

The study attempted to shed light on the correlation between brain hemispheric dominance and learner’s speaking performance. Data were obtained from 190 students of the second semester English students from three different universities in South Sulawesi. Statistic tests including Chi-Square and Kruskall-Wallis were administered to analyze the data. The study reveals that there is no significant correlation between brain hemispheric dominance and learner’s speaking performance. Moreover, the different categories of brain hemispheric dominance do not significantly contribute to learner’s speaking performance. Thus, this finding on one hand does not lend a support to previous finding by brain dominance theorists claiming that individuals who have different brain dominance tend to be different in doing specific tasks. However, on the other hand, it lends strong support to the recent findings in neuroscience community advocating that both hemispheres inter-connectedly work to process and deliver information.

Key words: brain hemispheric dominance; personal traits; cognitive styles; and speaking performance

INTRODUCTION

One of the mainstream theories in neuroscience adopted by many psychologists all

over the world is classification of two brain personalities based on how the brain works and

processes information. The idea that left and right brains are different in controlling specific

task has influenced many fields, including psychology, education, business, politics,

philosophy, history, military, and others. This theory believed that individuals are different in

terms of brain processing due to their brain hemispheric dominance.

The need to study human brain is conceivable and a must particularly when dealing

with a learning process. Hart (1983), states that teaching without a recognizing of how the

brain works could be analogical to designing a glove with no sense of what a hand looks like

its shape and how it moves. Hart mentions this analogy in order to emphasize his primary

point that if classrooms are places of learning, brain will then become the most crucial part to

the learning process, as it is the learning organ of human being. To achieve effective teaching

and learning goals, the brain must be understood and accommodated.

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mailto:[email protected]

Similarly, theorists of brain dominance have claimed that two hemispheres in human

brain work in different functions. According to Dubin (2001), brain cells are classified into

two main hemispheres that are differently and specifically functioned to respond visual

signals transmitted to the brain processor from the eyes. This is in line with Hoffelder and

Hoffelder (2007), claiming that the difference between left and right brain hemisphere for

most people is on mechanism of response in which left hemisphere functions to process

language, mathematical and analytical domain.

Moreover, language and brain are two inter-correlated items in which language

production is determined by complex neurological patterns. Chomsky (2006) states that there

are three components of biological system contributing to individual language development,

they are “genetic factors, experience, and principle not specific to the faculty of language”.

Chomsky further elaborated that human brain activation is potentially influenced by genetic

factors from which, biologically, language development is influenced by neural circuitry of

human brain, brain mechanism results in language instinct in human mind to perform

language competence, and it is coded as an innate linguistic knowledge that represents what

he labels “universal grammar”. Chomsky, however, does not specify that parts of human

brain function to process language mechanism. He focuses on “language competence” or

“knowledge of language” rather than how the language is processed in human brain.

However, his claim differs from what Saussure (1959) believes that the real purpose

of research in linguistics is to discern phenomena related to language knowledge (langue) and

extraneous events (parole). It is commonly known that understanding of grammatical rule or

language construction associated to human experience determines the process of language

production and perception. As a matter of fact, in his theory, Saussure ignores the fact that

complex neurological system contributes to how language is performed. This is in line with

Lieberman (2000) who points out that “language is a learned skill” that is controlled by “a

functional language system (FLS)” through distribution of physical activity in many parts of

complex human brain. He specifies that FLS serves to regulate spoken language production

and comprehension, which exists in only human brain and it connects with “other aspects of

cognition, motor control, and emotion”.

Studies in English education concerning on the improvement of learner’s speaking

performance has long been conducted to find out an effective teaching and learning method

to cater such a need. The involvement of neuroscience is considered to be another innovative

and progressive method that should be taken into account. Regardless of its lack popularity in

Indonesia, figuring out the contribution of brain hemispheric dominance to learner’s speaking

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performance can be regarded as a scholarly sounded empirical study, which is conceivable

and hence a must. This is due to the fact that the study explores human brain as an item that

potentially provides different perspectives and insights to shed light on the improvement of

quality of teaching-learning process, including those which concern with learner’s speaking

performance.

Furthermore, it can be said that all studies in English education which may concern

with methodology, curriculum, learner’s motivation and attitude, and other practical aspects

could all agree on the crucial part plays by the brain in the teaching-learning process as the

central body of instruction. The study is mainly aimed at figuring out the correlation between

brain hemispheric dominance and learner’s speaking performance and how the learners from

different categories of brain hemispheric dominance prepare strategies and organize their

ideas.

METHODS

Research Design

The study is descriptive quantitative in nature. Research design assigned learner’s

brain dominance and learner’s speaking performance to be the two correlated variables that

need to be investigated their interdependency. The first variable, brain dominance was

classified into five categories. They were strong left brain, moderate left brain, middle brain,

moderate right brain, and strong right brain. The second variable, speaking competence, was

scored based on the learners’ individual performance covered in a discussion session

employing Heaton’s (1988) rubric of speaking assessment consisting of accuracy, fluency,

and comprehensibility.

Data obtained from the two variables were analyzed in appropriate test of IBM

Statistical Package and Service Solution (SPSS 20) to find out level of significance in terms

of correlation between two variables and the difference among categories of brain

dominance. This research was conducted in English department, from three different

universities, one state university (Univesitas Islam Negeri Alauddin in Gowa) and two private

universities (Universitas Muhammadiyah Makassar in Makassar and Universitas

Cokroaminoto in Palopo), South Sulawesi, Indonesia.

Population and Sample

Silalahi (2012), states that population is units of selected sample that can be organism,

individuals or groups, society, organization, things, objects, phenomena, or reports which

have unambiguous definition of its characteristics. The population of this study consisted of

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the students at the second semester, English department, in three different universities; 75

students in Universitas Islam Negeri Alauddin Gowa from two classes, 325 students in

Universitas Muhammadiyah Makassar from ten classes, and 70 students in Universitas

Cokroaminoto Palopo from two classes. Total population was 470 students. The way of

taking the sample of this research was random sampling. The sample consisted of 63 students

from Universitas Islam Negeri Alauddin Gowa, 57 students from Universitas

Muhammadiyah Makassar, and 70 students from Universitas Cokroaminoto Palopo. Total

sample was 190 students (40. 43% of total population). To interview, total sample was 59

who consisted of 20 sample of moderate left brain, 20 sample of middle brain, and 19 sample

of moderate right brain since only three representative brain hemispheric dominance could be

found in this study.

Technique of Data Collection

After observing target population, brain hemispheric dominance test was randomly

distributed to the samples, two classes of each university. The test was from the alert scale of

cognitive style, designed by Crane (1989), from which he set the test that consisted of 21

questions. Each student was asked to choose one option of two options in each question. To

avoid students’ misunderstanding related to the meaning of the words on the test, the original

test in English version was translated into Indonesian. In doing brain dominance test, the

researcher clearly explained the meaning of items on the test to obtain accurate students’

preference related to the position of brain dominance. After score of the brain dominance test

was collected, student was asked to discuss in pair related to the favorite country. In this

session, the researcher distributed small paper as a guide of students to speak. On the paper,

the researcher wrote 4 questions related to the discussed topic (Favorite country) those are 1.

What is your favorite country, 2. To what aspects do you like in it? (Economy, people,

politics, law, landscape, business, tourism, military, technology, science, education,

entertainment, etc.), 3. Why do you like those aspects?, and 4. If you have an opportunity to

visit it, what will you do?. In the last session, students were asked to individually present

what they had discussed in pair without reading. They were allowed to improvise items on

the papers based on students’ prior knowledge. Their voice in speaking was recorded using

easy voice recorder, android program.

To find out how the students prepare strategies for presentation and how they

organize their ideas, representatives of students from three categories of brain hemispheric

dominance found in data analysis of brain dominance test were interviewed to identify what

the key points of students’ preparation and the way of organizing their ideas.

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Technique of Data Analysis

Classification of students’ brain dominance was based on specific instruction on

original source of the test adopted from the alert scale of cognitive style, Western Michigan

University, designed by Dr. Loren D. Crane in 1989. It consisted of 21 questions. One point

was given to the respondents who answer “A” for number “1, 2, 3, 7, 8, 9, 13, 14, 15, 19, 20,

21” and answer “B” for number “4, 5, 6, 10, 11, 12, 16, 17, 18”. Then, the sore was

computed to categorize brain hemispheric dominance based on the following classification:

0-4 : Strong Left Brain

5-8 : Moderate Left Brain

9-13 : Middle Brain

14-16 : Moderate Right Brain

17-21 : Strong Right Brain

(The Alert Scale of Cognitive Style by Crane, 1989)

Scoring system of speaking test was adopted criteria of speaking standard introduced

by Heaton in (1988), that divided criteria into three aspects namely accuracy, fluency, and

comprehensibility. A student’s score of each item (accuracy, fluency, and comprehensibility)

from three raters was converted into the following formula:

Speaking Score = T heGain Score of Eac hCriteria

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The main score of students was classified into the following table:

Score Classification Band Score

5.1 - 6 Excellent 6

4.1 - 5 Very Good 5

3.1 - 4 Good 4

2.1 - 3 Average 3

1.1 - 2 Poor 2

Table 1. Classification of students’ score

Data obtained was analyzed in IBM Statistical Package for the Service Solution

(SPSS) Statistics 20. To find out correlation between two variables, Pearson Chi-Square was

used. To normality of the data, One-Sample Kolmogorov-Smirnov Test and Shapiro-Wilk

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were used. Since finding of normality test showed that some data were not normally

distributed, testing homogeneity of variance in Levenne Test was not used, Analysis of

Variance (ANOVA) was replaced by Kruskal-Wallis Test and Independent T test was

replaced by Mann-Whitney Test as an alternative of post-hoc analysis. To find out what the

students did to prepare presentation and how they organized their ideas, data collected from

interview were analyzed and categorized in distribution of frequency and percentage.

FINDINGS

Data collected from three different universities were calculated based on scoring

system in original version of brain dominance test. The findings showed that in Universitas

Islam Negeri Alauddin there were 13 students of moderate left brain (the score ranged from 7

to 8), 40 students of middle brain (the score ranged from 9 to13), 8 students of moderate right

brain (the score ranged from 14 to 15), and 2 students of strong right brain (the score ranged

from 17 to 18). In Universitas Muhammadiyah Makassar there were 6 students of moderate

left brain (the score ranged from 6 to 8), 43 students of middle brain (the score ranged from 9

to 13), 8 students of moderate right brain (the score ranged from 14 to 16). In Universitas

Cokroaminoto Palopo there were 26 students of moderate left brain (the score ranged from 5

to 8), 41 students of middle brain (the score ranged from 9 to 13), and 3 students of moderate

right brain (their score was 14). Total of brain dominance score consisted of 44 students of

moderate left brain, 124 students of middle brain, 20 students of moderate right brain, and

only 2 students of strong right brain. From 189 samples, no one tended to the strong left

brain. Distribution of students’ brain dominance from second semester was dominated by

middle brain (65,3%) followed by moderate right brain(10,5%), moderate left brain (23,2%),

strong right brain (1 %) and strong left brain (0%).

Data collected from students’ performance were analyzed by three raters based on

accuracy, fluency, and comprehensibility. Each item provided score ranging from 1 to 6. 15

Students of moderate left brain obtained average score and 30 students of moderate left

obtained good score. To the middle brain, only 1 student obtained poor score, 53 students

obtained average score, 67 students obtained good score, and 3 students obtained very good.

To the moderate right brain, 9 students obtained average score, 8 students obtained good

score, and only 1 student obtained very good score. To the strong right brain, 2 students

obtained average score. The total of students’ score based on classification; no students

obtained very poor score, 1 student obtained poor score, 79 students obtained average score,

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106 students obtained good score, 4 students obtained very good score, and no student

obtained excellent and very poor score. Most of students obtained good score (55,8%)

followed by average score (41,6%), very good score (2,1%), and poor score (0,5%).

In statistical analysis, Total sample was 190, missing value 0, Mean score 3. 0758,

median 3.0, mode 2.90, standard deviation 0.44071, variance 0.194 and maximum score 5

(very good) and minimum 2 (poor). Distribution of frequency showed that the most gained

scores were 3, the lowest score was 2 and the highest was 5. Total of sample was 190.

Descriptive Statistic of Speaking Score is described in the following table:

NValid 190Missing 0

Mean 3,0758Median 3Mode 2,9Std. Deviation 0,44071Variance 0,194Minimum 2Maximum 5Sum 584,4

Table 2. Descriptive Statistic of Speaking Competence

The correlation between two observed variables, the brain hemispheric dominance

and speaking competence, was analyzed using appropriate test, Chi-Square Test, to find out

whether there was significant correlation between the brain hemispheric dominance and

speaking competence. Students score in the brain dominance test ranged from 5-18. The

score frequency of brain dominance distribution to the moderate left brain showed that 1

students obtained 5, 5 students obtained 6, 21 students obtained 7, and 18 students obtained 8.

To the middle brain, 22 students obtained 9, 36 students obtained 10, 22 students obtained 11,

22 students obtained 12, and 22 students obtained 13. To the moderate left brain, 14 students

obtained 14, 4 students obtained 15, and one students obtained 16. To the strong right brain 1

student obtained 17 and 1 student obtained 18. Based on these findings, students who had

frequency score less than 5 were excluded since Pearson Chi-Square accurately analyzed the

data for frequency of 5 and more. Students whose score were 5, 15, 16, 17, and 18 were

excluded to draw representative conclusion. Only three brain dominance categories were

computed into Pearson Chi-Square. The analysis of Chi-Square showed that Pearson Chi-

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Square Value was 158,897 to degree of freedom 165 at the level of significant 0,05.

Probability value (P) was 0,681 > 0, 05. Based on this analysis, H01 was accepted and it

could be concluded that there was no significant correlation between brain hemispheric

dominance and speaking competence. The Chi-Square analysis is described in following

table:

Value df Asymp. Sig. (2-sided)

Pearson Chi-Square 158,897a 168 ,681

Likelihood Ratio 149,455 168 ,845

Linear-by-Linear Association

,127 1 ,721

N of Valid Cases 182

Table 3. Chi-Square analysis of Brain Hemispheric Dominance and Speaking Competence

To find out, whether there was significant difference among three different categories

of brain dominance, data were computed into IBM Statistical Package and Service Solution

(SPSS 20). Appropriateness of statistical analysis, using parametric or non-parametric, was

determined by normality and homogeneity of the data. To analyze normality of the data,

Kolmogorov-Smirnov and Shapiro-Wilk were used.

In normality analysis, Kolmogorov-Smirnov showed that moderate left brain statistic

0.069, degree of freedom 45, and probability value (P) 0.200 > 0.05. It could be concluded

that speaking score for moderate left brain was normally distributed. To the middle brain,

statistic value was 0.163, degree of freedom 124 and probability value (P) 0.000 < 0.05. It

could be concluded that speaking score for middle brain was not normally distributed. To the

moderate right brain, statistic value was 0.219, degree of freedom 19 and probability value

(P) 0.017 < 0.05. It could be concluded that speaking score for moderate right brain was not

normally distributed. Shapiro-Wilk showed that moderate left brain statistic 0. 977, degree of

freedom 45, and probability value (P) 0.503 > 0.05. It could be concluded that speaking score

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for the moderate left brain was normally distributed. To the middle brain, statistic value was

0.949, degree of freedom 124 and probability value (P) 0.000 < 0.05. It could be concluded

that speaking score for middle brain was not normally distributed. To the moderate right

brain, statistic value was 0.883, degree of freedom 19 and probability value (P) 0.024 < 0.05.

It could be concluded that speaking score for the moderate right brain was not normally

distributed. . The analysis of normality test is described in the following table:

Brain Dominance

Kolmogorov-Smirnova Shapiro-Wilk

Statistic df Sig. Statistic df Sig.

Moderate Left ,069 45 ,200* ,977 45 ,503Middle ,163 124 ,000 ,949 124 ,000Moderate Right ,219 19 ,017 ,883 19 ,024

Table 4. Normality test of Speaking Competence

Since the normality test showed that score of middle brain and moderate right brain

were not normally distributed, it did not need to test homogeneity to conclude that the

appropriate test to find out whether there was significant difference among three different

categories of brain dominance was nonparametric test. In this analysis, Kruskal-Wallis was

used.

In output of Kruskal-Wallis Test, Chi-Square value was 0.487, degree of freedom 2,

and probability value was 0.784 > 0,05. Based on this output, H02 was accepted and it could

be concluded that there was no significant difference among different categories of brain

dominance. The output of Kruskal-Wallis Test is described in the following table.

Table 5. Output of Kruskall Wallis Test

To specifically analyze the level of significant among three found brain hemispheric

dominance (moderate left brain, middle brain, and moderate right brain), two independent

samples test, Mann-Whitney was used.

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Speaking Skill

Chi-Square ,487Df 2Asymp. Sig. ,784

In comparison between moderate left brain and middle brain, output of Mann-

Whitney test showed that speaking competence value was 2638.000, probability value (P)

0.587 > 0.05. It could be concluded that there was no significant difference between moderate

left brain and middle brain. The Mann-Whitney analysis is described in the following table:

Speaking Competence

Mann-Whitney U 2638Wilcoxon W 10388Z -0,543Asymp. Sig. (2-tailed) 0,587

Table 6. Mann-Whitney output of Moderate Left Brain and Middle Brain.

In comparison between moderate left brain and moderate right brain, output of Mann-


0.502 > 0.05. It could be concluded that there was no significant difference between moderate

left brain and moderate right brain. The Mann-Whitney analysis is described in the following

table:

Speaking CompetenceMann-Whitney U 382Wilcoxon W 572Z -0,672Asymp. Sig. (2-tailed) 0,502

Table 7. Mann-Whitney output of Moderate Left Brain and Moderate Right Brain.

In comparison between middle brain and moderate right brain, output of Mann-


0.858 > 0.05. It could be concluded that there was no significant difference between middle

brain and moderate right brain. The Mann-Whitney analysis is described in the following

table:

Speaking CompetenceMann-Whitney U 1064,5Wilcoxon W 1254,5Z -0,179

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Asymp. Sig. (2-tailed) 0,858

Table 8. Mann-Whitney output of Middle brain and Moderate Right Brain.

In preparation of students’ performance from moderate left brain, there were four

activities found based on students’ personal experience when they prepared strategies to

perform and present their ideas related to specific issues in English. In this study, from total

of 20 samples, 19 students (95 %) used dictionary, 18 students noted their ideas (90 %), 14

students memorized their concepts (70 %) and 6 students memorized key words (30 %).

Distribution of students’ preparation strategies from moderate left brain is described in the

following table:

Strategies of

Preparation Frequency

Percentag

e

Using dictionary (es) 19 95

Taking a note 18 90

Memorizing a concept 14 70

Memorizing Key words 6 30

Table 10. Distribution of students’ preparation from moderate left brain

In students’ organization of speaking performance from moderate left brain, there

were seven activities found based on students’ personal experience when they were speaking

and presenting their ideas related to specific issues in English. In this study, from total of 20

samples, 17 students (85 %) focused on grammar, 18 students focused on vocabulary (90 %),

16 students focus on pronunciation (80 %), 9 students focused on ideas (45 %), 8 students

spoke from general to specific (40 %), 12 students spoke from specific to general (60 %), and

18 students focused on fluency (90 %). Distribution of students’ organization in speaking

performance from moderate left brain is described in the following table:

Organization of

Speaking Frequency

Percentag

e

Focus on grammar 17 85

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Focus on vocabulary 18 90

Focus on pronunciation 16 80

Focus on ideas 9 45

General to specific 8 40

Specific to general 12 60

Focus on fluency 18 90

Table 11. Distribution of students’ organization in speaking performance from moderate left

brain

In preparation of students’ performance from middle brain, there were four activities

found based on students’ personal experience in preparing strategies to perform and present

their ideas related to specific issues in English. In this study, from total of 20 samples, 17

students (85 %) used dictionary, 16 students noted their ideas (80 %), 15 students memorized

their concepts (75 %) and 9 students memorized key words (45 %). Distribution of students’

preparation from middle brain is described in the following table:

Strategies of

Preparation Frequency

Percentag

e


Taking a note 16 80



Table 12. Distribution of students’ preparation from middle brain

Students’ organization of speaking performance from middle brain showed that there



samples, 15 students (75 %) focused on grammar, 17 students focused on vocabulary (85 %),

13 students focus on pronunciation (65 %), 12 students focused on ideas (45 %), 13 students

spoke from general to specific (65 %), 7 students spoke from specific to general (35 %), and

15 students focused on fluency (75 %). Distribution of students’ organization in speaking

performance from middle brain is described in the following table:

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Organization of

Speaking Frequency

Percentag

e




Focus on ideas 12 60




Table 13. Distribution of students’ organization in speaking performance from middle brain

In preparation of students’ performance from moderate right brain, there were four

activities found based on students’ personal experience when they were asked to perform and

present their ideas related to specific issues in English. In this study, from total of 19 samples,

15 students (75 %) used dictionary, 17 students noted their ideas (85 %), 9 students

memorized their concepts (45 %) and 14 students memorized key words (70 %). Distribution

of students’ preparation from moderate left brain is described in the following table:

Strategies of

Preparation Frequency Percentage


Taking a note 17 85



Table 14. Distribution of students’ preparation from moderate left brain

In students’ organization of speaking performance from moderate right brain, there



samples from moderate left brain, 9 students (45 %) focused on grammar, 16 students

focused on vocabulary (80 %), 13 students focus on pronunciation (65 %), 17 students

focused on ideas (85 %), 16 students spoke from general to specific (80 %), 4 students spoke

from specific to general (20 %), and 7 students focused on fluency (35 %). Distribution of

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students’ organization in speaking performance from moderate left brain is described in the

following table:

Organization of

Speaking Frequency

Percentag

e




Focus on ideas 17 85




Table 15. Distribution of students organization in speaking performance from moderate left brain

Based on the students’ distribution of frequency and percentage in strategies of

preparation, data above show that in part of using dictionaries, students of moderate left brain

(95 %) mostly use dictionaries to help them conceptualize their ideas in speaking

performance followed by middle brain (85 %) and moderate right brain (75 %). In taking a

note, students of moderate left brain (90 %) mostly note their concepts to prepare speaking

performance followed by moderate left brain (85 %) and middle brain (80 %). In memorizing

a concept, students of middle brain (75 %) mostly memorize concepts to prepare speaking

performance followed by moderate left brain (70 %) and moderate right brain (45 %). And in

aspect of memorizing key words, students of moderate right brain (70 %) mostly memorize

key words to help them express their ideas in speaking performance followed by middle brain

(45 %) and moderate left brain (30 %).

In presenting students’ ideas, tables of speaking organization above show that,

students of moderate left brain mostly focus on grammar (85 %) followed by middle brain

(75 %) and moderate right brain (45 %). Students of moderate left brain (90 %) also mostly

focus on vocabulary followed by middle brain (85 %) and moderate right brain (80 %). In

aspect of pronunciation, students of moderate left brain (80 %) mostly focus on it followed by

middle brain (65 %) and moderate right brain (65 %). Students of moderate right brain (85

%) mostly focus on ideas followed by middle brain (60 %) and moderate left brain (45 %).

Students of moderate right brain (80 %) mostly organize their ideas from general to specific

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followed by middle brain (65 %) and moderate left brain (40 %). Students of moderate left

brain (60 %) present their ideas from specific to general followed by middle brain (35 %) and

moderate right brain (20 %). And students of moderate left brain (90 %) mostly focus on

fluency followed by middle brain (75 %) and moderate right brain (35 %).

DISCUSSION

Analysis of data has been presented in the previous chapter. It shows that there was no

significant correlation between brain hemispheric dominance and speaking competence. This

finding differs from what the mainstream theorists of brain lateralization claim. An idea that

left and right brain are different in controlling specific task has influenced on many fields;

psychology, education, business, politics, philosophy, history, military, and others. This

theory provides a basic concept that individuals are different in terms of brain processing and

its dominance. Steinberg (1993) states that the brain consists of certain structures and

functions from which left hemisphere controls language, logical and analytical operations and

higher mathematics while the right hemisphere is superior at recognizing emotions,

recognizing faces and taking in the structures of things without more analysis.

Speaking activity involves oral production of language and listening comprehension.

If the ideas, brain dominance functions, were based on facts, the left brain students would be

better in speaking competence since they could control language by their logic. Most of

psychologists who support the theory of brain hemispheric dominance stand on the idea that

human brain consists of two hemispheres in which each side of the brain has specific

function. Everyone is believed that they are dominant in left, right, or balanced in terms of

how to do specific task based on brain function. In speaking performance, the cohorts of the

brain lateralization theory assume that left brain is superior in terms of language production

since language mechanism is developed in left hemisphere. Brown (2000), states that left

brain individuals tend to be better in speaking and writing expression. This concept derives

from previous findings that most of language disorders in human brain can be found in the

left hemisphere. There are few, however, neurologists propose different perspectives related

to how the brain works. They question classification of specific human activity associated

with brain function in both contrastive hemispheres. McGilchristh (2009), states that left and

right hemisphere play crucially important roles in almost process in human brain related to

mental activities. Both hemispheres inter-connectedly convey and transmitter information.

Based on this claim, production of language also involves right hemisphere and it cannot be

concluded that left hemisphere independently process information. He also states that the

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specific classification between two hemispheres is over generalization since brain function

involves complex interaction among particular sides of the brain.

Association of brain hemisphere with the personality traits and cognitive style in

which of brain lateralization theorists claim that left brain individuals tend to be detail

oriented, logical, sequential, rational, math and science, comprehending, analytical, objective,

using logic, facts rule, words and language, present and past, knowing, acknowledges,

knowing object name, reality based, forming strategy, order/pattern perception,

practical/planned, safe, cautious, and right brain individuals tend to big picture oriented,

random, intuitive, holistic, philosophy and spiritualism, getting the meaning, synthesizing,

subjective, using feeling, imagination rules, symbol and images, present and future, believes,

appreciates, knowing object function, fantasy based, presenting possibilities, spatial

perception, impetuous/spontaneous, adventurous, and carefree/risk taking. It is questioned

after recent research findings from neurologists, Nielsen and his colleagues, in University of

Utah 2013, whose research was aimed to find out patterns in human brain related to specific

task, showed different conclusion. Using Magnetic Resonance Imaging to 1011 samples in

various ages range from 7 to 29, Nielsen, et al. (2013), identified 7266 regions that showed

kinds of brain activities unrelated to personality traits and cognitive styles. They did not find

specific networks in the left and right hemisphere that process specific functions like what the

theorists of brain lateralization claim. Activities in left and right brain were certain mental

processes that connect each other. Based on their findings, they concluded that there was no

correlation between specific parts of the brain and personal preference of individuals since no

strong evidence that shows respondents’ brain activity related to specific preference based on

brain scanning outputs. This finding provides information that particular sides of the human

brain are inter-connected in processing and responding stimulus.

In speaking competence, in which brain lateralization theorist claim that production of

language is dominated by left hemisphere, Weaver (2013), states that, in production of oral

communication, patterns of speech involve complex hierarchical components that take place

on the different timing. Both sides of the brain are active to produce and deliver information.

It potentially results the same contribution to left and right hemisphere in speaking activity.

Thornbury (2005), states that, in aspect of mental processing, L1 and L2 speakers have

almost the same way to speak starting from conceptualizing, followed by formulating and

then articulating. All stages involve self monitoring. L1 and L2, however, differ in terms of

language and knowledge. Mother tongue vocabulary, grammatical rule, and understanding of

what the issue elaborated by the speaker influence on level of speaking skill.

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Similarity of the students’ score from various categories of brain dominance in

speaking competence shows that distribution of ability to produce oral language among

students who have different cognitive preference does not differ. They have the same

potential and capacity to improve their speaking competence. The different speaking

competence is possibly influenced by other factors.

Brain dominance test is designed based on students’ personality traits that influence

on preparation and the way of speakers organize their ideas. The different frequency and

percentage of students’ activities in speaking preparation and performance indicate that

students who have various personal traits and cognitive style tend to be different in the way

of performing speaking skill. Although recent finding shows that no correlation between

brain hemispheric dominance and physical activity of human brain, students’ personal traits

determine the way of students prepares and organize their ideas in performing speaking skill.

Various styles, however, do not significantly influence on quality of speaking skill from

academic perspective that consists of three categories; fluency, accuracy, and

comprehensibility.

In aspect of fluency, in English speaking skill, oral production of language is

determined by capacity of speakers spontaneously express their ideas. The more speakers

practice to talk, the more fluently they speak on specific issues, not practice of textual

grammatical rule and vocabulary, but practice how to communicate and produce oral

language since “automaticity” can be trained through high intensity of listening and

responding information and stimulus (Thornbury, 2005).

In aspect of accuracy, each language has its own structure and grammatical rules. In

context of learning English as a foreign language, for adult learners, mother tongue

influences on patterns of language expression. Thornbury (2005), states that accurate

utterance based on grammatical rule is determined by acquisition of information stored in

working memory. The more speakers read and learn grammar, the more accurate they utter

appropriate language structure

In aspect of comprehensibility, to understand what the speakers talk about,

articulation of the utterance must be clear. It can be acquired through practicing high intensity

of pronunciation based on appropriate sounds. The more speakers practice and listen a lot of

information, the more comprehensible oral language they produce.

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CONCLUSION

This current research provided evidence that oral production of language does not

significantly influenced by brain dominance that is associated to the personal traits and

cognitive style. Analysis of Kruskall-Wallis test showed that there was no significant

difference among categories of brain dominance in speaking score. Moderate left brain and

moderate right brain as two contrastive sides and having different functions claimed by

theorists of brain lateralization showed no evidence to supports the idea of the left and right

brain specific characteristics. Speaking is an activity that involves process of perceiving and

producing information. In context of foreign language learners, the way of students speak

was not significantly correlated to brain dominance. Findings on this research support the

recent finding that there is no correlation between specific areas on the brain and personal

preference based on brain scanning using resting state functional connectivity magnetic

resonance imaging. It rejected hypothesis that brain dominance was determined by personal

preference to specific activities from which brain dominance test was designed. Although,

classification of brain hemispheric dominance does not significantly influence quality of

speaking skill, it determines the way of students prepare their presentation and organizing

ideas based on cognitive styles that have been divided by theorist of brain hemispheric

dominance. Practice to respond stimuli and produce oral language contributes to

improvement of students’ automaticity to be fluent in speaking skill. Learning grammatical

rule, structure, and vocabulary use play significant role to accuracy of speakers.

Comprehension of what the speakers talk about can be acquired through practicing of

pronunciation and articulation.

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Documents

· Web viewTHE CORRELATION BETWEEN BRAIN HEMISPHERIC DOMINANCE AND LEARNERS’ ENGLISH SPEAKING PERFORMANCE Abdul Hakim Yassi1 and Umar2 1Cultural Science Faculty of Hasanuddin University