THE CORRELATION BETWEEN BRAIN HEMISPHERIC DOMINANCE AND LEARNERS’ ENGLISH SPEAKING PERFORMANCE
Abdul Hakim Yassi1 and Umar2
1Cultural Science Faculty of Hasanuddin University of Makassar, Indonesia
2Faculty of Letters of Satria University of Makassar, Indonesia
Abstract
The studyattempted 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 thatthere 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 handdoes 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 supportto 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 totheir 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 arecognizing 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 isthe learning organ of human being. To achieve effective teaching and learning goals, the brain must be understood and accommodated.
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 withHoffelder 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 theprocess 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 neuroscienceis 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 brainhemispheric dominance to learner’s speaking 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 outthe 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 isdescriptive 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 employingHeaton’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 NegeriAlauddin in Gowa) and two private universities (UniversitasMuhammadiyah Makassar in Makassar and UniversitasCokroaminoto 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 the students at the second semester, English department, in three different universities; 75 students in Universitas Islam NegeriAlauddinGowa from two classes, 325 students in UniversitasMuhammadiyah Makassar from ten classes, and 70 students in UniversitasCokroaminotoPalopo 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 NegeriAlauddinGowa, 57 students from UniversitasMuhammadiyah Makassar, and 70 students from UniversitasCokroaminotoPalopo. 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.
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 =
The main score of students was classified into the following table:
Score / Classification / Band Score5.1 - 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 were used. Since finding of normality test showed that some data were not normally distributed, testing homogeneityof variance inLevenne 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 NegeriAlauddin 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 UniversitasMuhammadiyah 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 UniversitasCokroaminotoPalopo 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, 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:
N / Valid / 190Missing / 0
Mean / 3,0758
Median / 3
Mode / 2,9
Std. Deviation / 0,44071
Variance / 0,194
Minimum / 2
Maximum / 5
Sum / 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-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 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: