LOGICO-MATHEMATICO INTELLIGENCE AND ACHIEVEMENT IN COMPUTER SCIENCE OF DEGREE STUDENTS
Ms.M.Kanmani[1] Dr.P.Annaraja[2]
ABSTRACT
This paper reports on the Logico-mathematico Intelligence and academic achievement of computer science students. The sample consisted of 59 B.Sc computer science students. A scale on Logico-mathematico intelligence 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 shows that among the sample, there is a low negative correlation between the Logico-mathematico Intelligence and achievement in computer science of degree students.
Introduction
For over two thousand years civilizations have been discussing the existence and importance of mental powers-capacities reflecting intelligence or the deployment of the mind, which led to a rise in the desire to learn more about the human brain and human potential. In the early 70’s, Dr.Howard Gardner believed that there was a persuasive evidence for the existence of several relatively autonomous human intellectual competencies which he referred to as “human intelligences”. Logical – Mathematical Intelligence is the second of the multiple intelligences, typically emphasized in schools and colleges; this intelligence includes not only the ability to use numbers but reasoning ability and scientific thinking ability. The current efforts to develop critical thinking skills also dovetail with this intelligence. Any activity which relies on the development of a logical sequence of steps is utilizing this intelligence. Careers which draw on this intelligence include mathematician, accountant, scientific researcher, and computer programmer. Some of the researchers in the field of education and psychology were tried find out the influence of different intelligence on education. Woods and Gary Cornelivs (2004) conducted a study on students’ perceptive of web based technologies, principles of good practice and multiple intelligence. The findings of the study revealed that there is significant correlations existed between student satisfaction with web based instruction and student rating of web hand technologies, principles of good practice, and multiple intelligence Discussion board, course information, e-mail, web links and announcements features received higher rating than syllabus, Journal file exchange, multimedia and homepage features. Mackic and Russell Keith (2005) conducted the study among North Carolina community college students. This study revealed that there was no significant relation between logical mathematical intelligence and linguistic intelligence and also there was not a significant relation between spatial intelligence and logical mathematical intelligence. Though there are much studies have been done in multiple-intelligences, but this study is unique in its trait to find out the influence of logical-mathematical intelligence on achievement in computer science of degree students, which is considered as one of the important needed intelligence in program development.
Objectives of the study
1. To find out the level of logico-mathematico intelligence among computer science degree students.
2. To find out the level of academic achievement in computer science of degree students
3. To find out the relationship between logico-mathematico intelligence and academic achievement of computer science degree students
The above said objectives are achieved in terms of demographic variables: gender, type of the college, nature of the college, educational qualification of the parents and occupation of the parents
Null Hypotheses
1.1. There is no significant difference in logico-mathematico intelligence of computer science degree students with respect to their
i. Gender
ii. Type of the college
iii. Nature of the college
1.2 There is no significant association in logico-mathematico intelligence of computer science degree students with respect to their
i. Educational Qualification of Parents
ii. Occupation of Parents
2.1. 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
2.2. There is no significant association in the academic achievement of computer science degree students with respect to their
i. Educational Qualification of Parents
ii. Occupation of Parents
3.1. There is no significant influence of logico-mathematico intelligence on academic achievement of computer science degree students.
Method: Survey method of research was adopted for the 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, Palayamkottai were selected for the study.
Tool: Logico-mathematico intelligence scale developed by Kanmani(2008) and Annaraja(2008) was used for data collection.
Data Analysis: Percentage, t- test, F- test, Chi square test and Karl Pearson product moment co-efficient of correlation were used for analyzing the data.
Table 1: Logico-mathematico intelligence and Achievement in Computer Science of Degree Students
S.No | Level of Logico-mathematico intelligence | No. of Students | % | Academic Achievement | No. of Students | % |
1. | High | 10 | 16.94 | High | 8 | 13.55 |
2 | Moderate | 28 | 47.45 | Moderate | 38 | 64.40 |
3. | Low | 21 | 35.59 | Low | 13 | 22.00 |
4 | Total | 59 | 100 | Total | 59 | 100 |
It is inferred from the above table that 16.94% of computer science students have high logico-mathematico intelligence, 47.45% of them have moderate logico-mathematico intelligence and 35.59% of them have low level of logico-mathematico intelligence.
Further, it is inferred that 13.55% students have high academic achievement, 64.40% students of them have moderate and 22% of them have low level of academic achievement in computer science.
Table 2: Difference in Logico-mathematico intelligence of Computer Science Degree Students
Factor | N | Mean | S.D | t-Value | df | Remark* | |
Gender | Male | 17 | 13.65 | 3.10 |
1.582 |
57 |
NS |
Female | 42 | 15.10 | 3.38 | ||||
Type of College | Co-education | 32 | 15.34 | 3.507 | 1.713 | 57 | NS |
Women | 27 | 13.89 | 3.017 | ||||
Nature of College | Govt. | 32 | 15.34 | 3.507 | 1.713 | 57 | NS |
Govt. Aided | 27 | 13.89 | 3.017 | ||||
*Significant at 0.05 level of‘t’ value is 2.02
It is inferred from the above table that the calculated‘t’ values (1.582 and 1.713) are less than the table value of‘t’ (2.02). Hence the null hypotheses are accepted. Thus there is no significant difference between male and female computer science students’ logico-mathematico intelligence.
Table 3: Association between Logico-mathematico intelligence of Degree Students and Educational Qualification and Occupation of their Parents
Factors | Logico-mathematico intelligence |
| df | Calculated chi-square Value | Remarks*
| |||
Low | Moderate | High | Total | |||||
Educational Qualification of Parents | illiterate | 3 | 8 | 10 | 21 | 4 | 6.149 | NS |
School Education | 6 | 14 | 11 | 31 | ||||
College Education | 1 | 6 |
| 7 | ||||
Total | 10 | 28 | 21 | 59 | ||||
Occupation of parents | Coolie | 9 | 14 | 15 | 38 | 4 |
6.787 |
NS |
Government Employee | 1 | 10 | 3 | 14 | ||||
Business |
| 4 | 3 | 7 | ||||
Total | 10 | 28 | 21 | 59 | ||||
*Significant at 0.05 level of c2 value is 9.488
It is inferred from the above table that the calculated ‘c2’ values (4.942 and 4.545) 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 their parents, occupation of their parents and logico-mathematico intelligence of computer science students.
Table 4: Difference in 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 | |||
*Significant at 0.05 level of‘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 male and female students, government aided and government college students, women’s and co-education college students’ achievement in computer science.
Table 5: Association between Academic Achievement and Educational Qualification and Occupation of their 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 their parents, occupation of their parents and achievement in computer science of the degree students.
Table 6: Correlation between Logico-mathematico intelligence and Academic Achievement Computer Science Degree Students
| Remarks* | ||
Meta cognition and Academic Achievement | df = 57 | r = -0.067 | NS |
* Significant at 0.05 levels is 0.250
It is inferred from the above table that the calculated ‘r’ value (-0.067) is less than the table value (0.0250). Hence the null hypothesis is accepted. Thus there is no significant influence of logico-mathematico intelligence on achievement of computer science degree students.
Findings
1.1. 16.94% of computer science students have high level of logico-mathematico intelligence
1.2. Male and Female computer science students do not differ in their logico-mathematico intelligence
1.3. There is no significant difference between the computer science students studying in co-education colleges and women’s colleges in their logico-mathematico intelligence
1.4. There is no significant difference between the government and government aided college students in their logico-mathematico intelligence
1.5. There is no significant association between the logico-mathematico intelligence and educational qualification of parents of computer science students
1.6. There is no significant association between the logico-mathematico intelligence and occupation of the parents of computer science students
2.1 78.95% of students have high level of achievement in computer science.
2.2 Male and female computer science students do not differ in their achievement in computer science.
2.3 There is no significant difference between government and government aided college students’ achievement in computer science.
2.4 There is no significant difference between the students from Women’s and Co-education colleges in their achievement in computer science.
2.5 There is no significant association between academic achievement in computer science and educational qualification of the parents.
2.6 There is no significant association between academic achievement in computer science and Occupation of the parents.
3.1 There is a low negative correlation between logico-mathematico intelligence and achievement of computer science degree students.
Suggestions
We suggest the following teaching strategies to foster logical/mathematical intelligence of the computer science students
i. Learning opportunities for problem solving using critical thinking skills can be structured for teaching the abstract concepts like pointers and arrays in computers
ii. Project using scientific methods can be conducted to foster problem solving abilities among the students for the development of efficient computer softwares.
iii. Opportunities should be given to the learners especially to compare and contrast objects (physical things) and concepts (mental things) in the classrooms
iv. Have the students to be participated in an empirical study based on the scientific method
v. Have the students to analyze a series of events or phenomena for underlying patterns in the new learning concepts
vi. Technological tools and software can be used in the classroom teaching based on the logical-mathematical intelligence which can lure students into topics they may have previously disliked
vii. Interactive white boards enable teachers to present multi-sensory materials that will be more easily understood and absorbed by a wider audience.
viii. Using multimedia to include audio, video, text and images as parts of a lesson presentation or as a means of learners presenting their work offers a significant means of addressing the needs of different of learning styles
References
1. Gardner, Howard, 1983, “Frames of Mind”, New York, Basic Books
2. Mackic, Russell keith (2005). The study conducted North Carolina community college. Vol.66, no.5, p.3879A.
3. Shukla, K.C (2005). Practical Psychology, New Delhi: Common wealth publishers.
4. Woods and Gary Cornelivs (2004). A study of students’ perceptive of web based technologies, principles of good practice and multiple intelligence. Vol.66, no.5, p.501A.
Websites
1. http://www.p3.harvard.edu.com
3. http//www.ed.gov/database/CRICDigests/ed.410226.html
4. http://www.vwsp.edu/adu/acad/educ/wilson.com
5. http://www.newhorizons.org.com
6. http://www.cortland.edu/psych/millogical.html
[1] Lecturer, Department of Education, Manonmaniam Sundaranar University
[2] Reader in Mathematics, St.Xavier’s College of Education, Palayamkottai
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