Wednesday, March 10, 2010

BRAIN DOMINANCE AND ACHIEVEMENT IN COMPUTER SCIENCE OF DEGRE

BRAIN DOMINANCE AND ACHIEVEMENT IN COMPUTER SCIENCE OF DEGREE STUDENTS

M.Kanmani[1]                                                                                                                          Dr.P.Annaraja[2]

 

ABSTRACT

This study is designed to find out the influence of brain dominance and achievement in computer science of degree students. The sample consisted of 59 B.Sc computer science students. Brain dominance tool was used to get the data from the students .Percentage analysis, Pearson-Product moment correlation co-efficient, t-test, F-test and chi-square tests were used for analyzing the data. The result clearly shows that among the sample, there are only three types of brain dominance present namely moderate left-brain, middle brain and strong right brain. The study reveals that   the middle brain dominance students have better achievement in computer science  than the  moderate left brain and strong right brain dominant students.

 

Introduction

The Kothari Education Commission (1966) rightly said that The destiny of India is being shaped in Classroom. The shape, undoubtedly, will depend on what goes on, in the classroom and how does it go on? The quality of teaching behavior, in its turn, depends upon the level of equipment of teachers with necessary skills in designing and handling teaching behaviors. Since independence, India has been attempting to raise the living standard of her inhabitants. The success of such efforts depends largely on the quality of human resources, which in turn is influenced by the standard of education in the country.

Education implies insight experience and adjustment on the part of man, as he is stimulated towards growth and development. Thus, education is an essential base of good life. Froebel(1842) said that “Education is a process through which child makes it internal and external development. To develop the child, teacher plays the most prominent role in moulding the habits, taste and character of the pupils. The teaching method and technology used in the classroom also have an impact on learning. Regarding cognitive, Affective and Psychomotor learning, the right, left and the central brains are playing very predominant roles. Though it dominates all types of learning and helps to achieve, now the question arises is how the brain dominates the academic achievement of degree students in computer science? Here are some of the research findings which support this study. Lunn, Karen (2004) studied “Data assimilation in Brain deformation modeling.  Evans, Sheryl (2004) studied “Study habits of college students and their perceptions of the impact of brain – based attention strategies on their independent study time. The study revealed that   meta-cognitive study strategies (both cognitive and effort management) and higher order thinking strategies should be taught and supported in colleges. , Virtue, Van den Broek (2005) conducted a study on Brain and Language. The major finding of the study was the hemisphere processing of anaphors when readers activate multiple antecedents. Marini, Cariomagno (2005) conducted a study on the role played by the right hemisphere in organization of complex textual structures. Greenwood Roy (2006) conducted a study on educator acquisition and application of recent neurological and cognitive research. One of the findings reveals that a need exists for the establishment of reliable sources of information as well as more opportunities for educator to learn about the findings from neurology and cognitive psychology. The trend analysis in this area of research shows that not much work especially in India has been done to find out the type of brain dominance and academic achievement in computer science of degree students. Considering these points the present study has been taken up.

Objectives of the study

 

1. To find out the type of brain dominance among computer science degree students.

2. To find out whether there is any significant difference in the academic achievement of  computer science degree students with respect to their

i.                  Gender

ii.                Type of the college

iii.              Nature of the college

3. To find out whether there is any significant association in the academic achievement of computer science degree students with respect to their

i.                  Educational Qualification of Parents

ii.                Occupation of Parents

4. To find out the influence of brain dominance on academic achievement in computer science of degree students.

 

 

 

Null Hypotheses

 

1. There  is no  significant difference in the academic achievement of  computer science degree students with respect to their

i.                  Gender

ii.                Type of the college

iii.              Nature of the college

iv.              Type of Brain Dominance

2. There is no significant association in academic achievement of computer science degree students with respect to their

 

i.                  Educational Qualification of Parents

ii.                Occupation of Parents

3. There is no significant influence of brain dominance on academic achievement in computer science of degree students.

 

Method: Survey method of research has been used in the present study

 

Sample: Randomly selected 59 first year computer science students from Rani Anna College of Arts and Science, Tirunelveli and St. John’s College of Arts and Science, Palyamkottai are selected for the study.

Tools: Brain Dominance was developed from the Alert scale of cognitive style by               Dr. Loren D. Crane. It consists of 21 items. Test-retest method was used to establish co-efficient of reliability of the tool and it was found to be 0.642.

Data Analysis: Percentage, t- test, F- test, Chi square test and Karl Pearson product moment co-efficient of correlation are used for analyzing the data.

Table 1: Type of Brain Dominance of Computer Science Students

 

S.No

Type of Brain Dominance

No. of Students

Percentage

1.

Moderate Left Brain

8

13.6

2

Middle Brain

47

79.7

3.

Strong Right Brain

4

6.78

It is inferred from the above table that 13.6% of computer science students have moderate left brain dominance, 79.7% students have middle brain dominance and 6.78% students have strong right brain dominance.

 

Table 2: Significant difference in Academic Achievement of Computer Science Students

Factor

N

Mean

S.D

t-Value

Remark*

Gender

Male

17

5.88

2.088

 

0.593

Not Significant

Female

42

5.52

2.144

Type of College

Co-education

32

67.06

8.791

 

0.147

Not Significant

Women

27

66.73

8.427

Nature of College

Govt.

32

67.06

8.791

0.147

Not Significant

Govt. Aided

27

66.73

8.427

Factor

Df

F – Value

Remarks*

Type of Brain dominance

Moderate Left Brain

 

 

2

56

 

 

 

1.299

 

 

Not Significant

Middle Brain

Moderate Right Brain

*Significant at 0.05 level of F value is 3.32 and t value is 2.02

 

It is inferred from the above table that the calculated “t” values (0.593, 0.147, and 0.147) are less than the table values of “t” (2.02). Hence the null hypotheses are accepted. Thus, there is no significant difference between the boys and girls, government aided and government college students, women’s and co-education college students’ academic achievement in computer science.

 

It is inferred from the above table that the calculated ‘F’ values (0.199, 2.793, and 1.299) are less than the table value of ‘F’ (3.32). Hence the null hypotheses are accepted. Thus there is no significant difference in the academic achievement of computer science students with respect to Educational qualification and the occupation of the parents.

 

 

 

 

 

Table 3: Chi-square showing the association between the Academic Achievement, Educational Qualification and occupation of the parents

 

Factors

Academic Achievement

 

df

Calculated

chi-square Value

Remarks*

 

 

Low

Moderate

High

Total

Educational  Qualification of Parents

illiterate

4

13

4

21

4

1.364

NS

School

Education

8

20

3

31

College Education

1

5

1

7

Total

13

38

8

59

Occupation

of parents

Coolie

8

26

4

38

 

4

 

 

 

 

4.775

 

 

 

 

NS

Government Employee

5

7

2

14

Business

0

5

2

7

Total

13

38

8

59

*Significant at 0.05 level of c2 value is 9.488

 

It is inferred from the above table that the calculated ‘c2’ values (1.364 and 4.775) are less than the table value of ‘c2’ (9.488). Hence the null hypotheses are accepted. Thus there is no significant association between the Educational Qualification of the parents, Occupation of the parents and academic achievement of computer science students.

Table 4: Correlation between Brain Dominance and Academic Achievement of Computer Science Students

 

Remarks*

Brain Dominance and Academic Achievement

df = 57

R= 0.168

NS

                                                        * Significant at 0.05 levels is 0.250

 

It is inferred from the above table that the calculated “r” value 0.168 is less than the table value of “r” (0.250). Hence the null hypothesis is accepted. Thus, there is no significant correlation between the brain dominance and academic achievement of computer science students.

Findings and Interpretations

 

I.       It is found out from the above study that, 13.6% of computer science students have moderate left brain dominance, 79.7% students have middle brain dominance and 6 .78% students have strong right brain dominance.

II.     It is found out from the above study that 78.95% of students have good level, and 22% of the students have low level of academic achievement in computer science respectively.

III.   There is no significant difference between the boys’ and girls’ achievement in   computer science. However, while comparing the mean values (5.88, 5.52); the boys’ performance in compute science is greater than the girls performance. Hence from the study it is found out that the performance of boys is greater than the performance of girls in computer science

IV.  There is no significant difference between government and government aided college students’ achievement in computer science. However, while comparing the mean values (67.06, 66.73), the government college students’ achievement is greater than the Government Aided college students’ in computer science. Hence from the study it is found out that the performance of government college students is greater than the Government Aided college students in computer science.

V.    There is no significant difference between Women’s and Co-education college students’ achievement in computer science. While comparing the mean values (67.06, 66.73), the students studying in co-education colleges have greater achievement than Women’s college students in computer science.

VI. There is no significant difference between the moderate Left brain dominant, middle brain dominant and strong right brain dominant students’ achievement in computer science. While comparing their mean scores the middle brain dominant students’ achievement in computer science (68) is greater than the moderate left brain and strong right brain (66 and 61).

       VII. There is no significant association between academic achievement in computer science and educational qualification of the parents.

VIII. There is no significant association between academic achievement in computer science and Occupation of the parents.

IX. There is no significant influence of brain dominance on academic achievement in computer science of degree students.

 

 

Suggestions

i.                                                                           Innovative teaching strategies can be incorporated in curriculum.

ii.                                                                         If Virtual reality is used in classrooms, it will help the students to understand even the difficult topics in a better way.

iii.                                                                       The teacher can adopt different types of techniques namely CAI, CBI, interactive white board methods and blended instructions according to their learning style and the type of dominance of brain which influences their learning at maximum level.

iv.                                                                       More number of practical classes and demonstration methods can be adopted to improve their level of learning

v.                                                                         POWERPOINT presentations can be used to explain the architecture of computers

vi.                                                                       Intelligent Tutorial System can be followed

Bibliography

 

i.       Aggarwal (1996) Theory and Principles of education, Vikas publishing house, New Delhi.

ii.     Aggarwal (2000) Essential of educational Psychology, Vikas publishing house Pvt. Limited, New Delhi.

iii.   Best John, James (1998) Research in Education, Practice Hall of India Pvt. Ltd., New Delhi.

iv.   Evans, Sheryl (2004) Study habits of college students and their perceptions of the study time , Dissertation Abstract International, Vol.66, No.2, P.510-A

v.     Greenwood, Roy (2006) Educator acquisition and application of recent neurological and cognitive research, Dissertation Abstract International, Vol.68, No.1, P.82-A.

vi.   Lunn, Karen (2004) Data assimilation in brain deformation modeling, Dissertation Abstract International, Vol.65, No.3, P.1425-A.

vii. Marini, Cariomagno (2005), The role played by the right hemisphere in organization of complex textual structures, Dissertation Abstract International, Vol.66, No.7, P.2630-A

viii.           Mishra, Mohanty (1998) Teacher Education, Surya publications, Meerut.

ix.   Taschetta (1990) The whole Brain approach in teaching engineering technology, Asia publishing House, New York.

x.     Virtue, Van den Broek (2005), Brain and Language, Dissertation Abstract International, Vol.66, No.7, P.2630-A

 

 

 

 

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[1] Lecturer, Department of Education, Manonmaniam Sundaranar University, Tirunelveli-12

[2] Reader in Mathematics, St.Xavier’s College of Education, Palayamkottai


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