Correlational Analysis between Brain Dominances and Multiple Intelligences
Aim of this research study is to investigate and
establish the characteristics of brain dominances (BD) and multiple
intelligences (MI). This experimentation has been conducted for the
sample size of 552 undergraduate computer-engineering students. In
addition, mathematical formulation has been established to exhibit
the relation between thinking and intelligence, and its correlation has
been analyzed. Correlation analysis has been statistically measured
using Pearson’s coefficient. Analysis of the results proves that there
is a strong relational existence between thinking and intelligence.
This research is carried to improve the didactic methods in
engineering learning and also to improve e-learning strategies.
[1] David Yun Dai, “Reductionism versus Emergentism: A framework for
understanding conceptions of giftedness,” Roeper Review, vol. 27,
pp.144-151, 2005. doi: 10.1080/02783190509554308.
[2] C. Spearman, “General Intelligence, Objectively Determined and
Measured,” American Journal of Psychology, vol. 15, pp. 201-293,
1904. doi:10.2307/1412107
[3] Thurstone, L. L, “Multiple-Factor Analysis,” Journal of Clinical
Psychology, vol. 4, pp. 25-42, 1947. doi: 10.1002/1097-
4679(194804)4:2<224::AID-JCLP2270040225>3.0.CO;2-7
[4] Sternberg, R.J, “Beyond IQ: A Triarchic Theory of Human Intelligence”.
NewYork: Cambridge University Press. 10-32, 1985.
[5] Gardner H. and Hatch T, “Educational implications of the theory of
multiple intelligences,” Education Researcher, vol. 18, pp. 4-10, 1989.
doi: 10.3102/0013189X018008004
[6] Karl Openshaw and Celia B. Stendler, “Aspects of Piaget’s Theory That
Have Implications for Teacher Education,” Journal of Theacher
Education, vol. 16, pp. 329-335, 1965.
doi: 10.1177/002248716501600316
[7] Katherine Benziger, “The BTSA User Manual: A Guide to the
Development, Validation and Use of the Benziger Thinking Styles”,
BookSurge Publishing, Edition 3, pp. 20-30, 2010.
[8] Bostrom N, Sandberg A, “Cognitive enhancement: methods, ethics,
regulatory challenges,” Springer, vol. 15, pp. 311-41, 2009.
doi: 10.1007/s11948-009-9142-5
[9] Bloom, B.S, “Stability and Change in Human Characteristics”. New
York: Wiley, 1964.
[10] Yingxu Wang, Ying Wang, Shushma Patel and Dilip Patel, “A Layered
Reference Model of the Brain (LRMB)”. IEEE Transactions on systems,
Man, and Cybernetics – Part C: Applications and Reviews, vol. 36,
2006. doi: 10.1109/TSMCC.2006.871126
[11] Yingxu Wang, Dong Liu and Ying Wang, “Discovering the Capacity of
Human Memory,” Brain and Mind, vol. 4, pp. 189-198, 2003.
[12] Perlovsky, L.I, “Model-based neural network for pattern recognition,”
Proceedings of the World Congress on Neural Networks, pp. 380–383,
1996.
[13] Yingxu Wang, “The Theoretical Framework and Cognitive Process of
Learning,” Proc. 6th IEEE Int. Conf. on Cognitive Informatics, 2007.
[14] Beth A. Visser, Michael C. Ashton, Philip A. Vernon, “g and
measurement of Multiple Intelligences: A response to Gardener.
Intelligence,” Elsevier, vol. 34, pp. 507-510, 2006.
doi:10.1016/j.intell.2006.04.006
[15] Jonathan Interton, “Typology of Knowledge, skills and competencies:
clarification of the concept and prototype”, Luxembourg Official
Publications, Europe, pp. 6-7, 2006.
[16] Neisser, U., Boodoo, G., Bouchard, T. J., Jr., Boykin, A. W., Brody, N.,
Ceci, S. J., Urbina, S, “Intelligence: Knowns and unknowns,” American
Psychologist, vol. 51, pp. 77–101, 1996.
doi:10.1037/0003-066X.51.2.77.
[17] Donald Borrett, Sean Kelly and Hon Kwan, “Phenomenology,
dynamical neural networks and brain function,” Philophical Psychology,
vol. 13, pp. 213-228, 2000. doi: 10.1080/09515080050075690
[18] Hicklin, W. J, “A model for mastery learning based on dynamic
equilibrium theory,” Journal of Mathematical Psychology, vol. 13, pp.
79-88, 1976. doi:10.1016/0022-2496(76)90035-3
[19] http://ekluvya.adithyatech.edu.in
[20] Richard E. Nisbett, Joshua Aronson and Clancy Blair, William Dickens,
James Flynn, Diane F. Halprn, Eric Turkheimer, “Intelligence - New
Findings and Theoretical Developments,” American Psychologist, vol.
67, pp. 130-159, 2012. doi: 10.1037/a0026699
[21] McEwen, B. S, “The neurobiology of stress: From serendipity to clinical
relevance,” Brain Research, vol. 886, pp. 172–189, 2000.
doi:10.1016/S0006- 8993(00)02950-4.
[1] David Yun Dai, “Reductionism versus Emergentism: A framework for
understanding conceptions of giftedness,” Roeper Review, vol. 27,
pp.144-151, 2005. doi: 10.1080/02783190509554308.
[2] C. Spearman, “General Intelligence, Objectively Determined and
Measured,” American Journal of Psychology, vol. 15, pp. 201-293,
1904. doi:10.2307/1412107
[3] Thurstone, L. L, “Multiple-Factor Analysis,” Journal of Clinical
Psychology, vol. 4, pp. 25-42, 1947. doi: 10.1002/1097-
4679(194804)4:2<224::AID-JCLP2270040225>3.0.CO;2-7
[4] Sternberg, R.J, “Beyond IQ: A Triarchic Theory of Human Intelligence”.
NewYork: Cambridge University Press. 10-32, 1985.
[5] Gardner H. and Hatch T, “Educational implications of the theory of
multiple intelligences,” Education Researcher, vol. 18, pp. 4-10, 1989.
doi: 10.3102/0013189X018008004
[6] Karl Openshaw and Celia B. Stendler, “Aspects of Piaget’s Theory That
Have Implications for Teacher Education,” Journal of Theacher
Education, vol. 16, pp. 329-335, 1965.
doi: 10.1177/002248716501600316
[7] Katherine Benziger, “The BTSA User Manual: A Guide to the
Development, Validation and Use of the Benziger Thinking Styles”,
BookSurge Publishing, Edition 3, pp. 20-30, 2010.
[8] Bostrom N, Sandberg A, “Cognitive enhancement: methods, ethics,
regulatory challenges,” Springer, vol. 15, pp. 311-41, 2009.
doi: 10.1007/s11948-009-9142-5
[9] Bloom, B.S, “Stability and Change in Human Characteristics”. New
York: Wiley, 1964.
[10] Yingxu Wang, Ying Wang, Shushma Patel and Dilip Patel, “A Layered
Reference Model of the Brain (LRMB)”. IEEE Transactions on systems,
Man, and Cybernetics – Part C: Applications and Reviews, vol. 36,
2006. doi: 10.1109/TSMCC.2006.871126
[11] Yingxu Wang, Dong Liu and Ying Wang, “Discovering the Capacity of
Human Memory,” Brain and Mind, vol. 4, pp. 189-198, 2003.
[12] Perlovsky, L.I, “Model-based neural network for pattern recognition,”
Proceedings of the World Congress on Neural Networks, pp. 380–383,
1996.
[13] Yingxu Wang, “The Theoretical Framework and Cognitive Process of
Learning,” Proc. 6th IEEE Int. Conf. on Cognitive Informatics, 2007.
[14] Beth A. Visser, Michael C. Ashton, Philip A. Vernon, “g and
measurement of Multiple Intelligences: A response to Gardener.
Intelligence,” Elsevier, vol. 34, pp. 507-510, 2006.
doi:10.1016/j.intell.2006.04.006
[15] Jonathan Interton, “Typology of Knowledge, skills and competencies:
clarification of the concept and prototype”, Luxembourg Official
Publications, Europe, pp. 6-7, 2006.
[16] Neisser, U., Boodoo, G., Bouchard, T. J., Jr., Boykin, A. W., Brody, N.,
Ceci, S. J., Urbina, S, “Intelligence: Knowns and unknowns,” American
Psychologist, vol. 51, pp. 77–101, 1996.
doi:10.1037/0003-066X.51.2.77.
[17] Donald Borrett, Sean Kelly and Hon Kwan, “Phenomenology,
dynamical neural networks and brain function,” Philophical Psychology,
vol. 13, pp. 213-228, 2000. doi: 10.1080/09515080050075690
[18] Hicklin, W. J, “A model for mastery learning based on dynamic
equilibrium theory,” Journal of Mathematical Psychology, vol. 13, pp.
79-88, 1976. doi:10.1016/0022-2496(76)90035-3
[19] http://ekluvya.adithyatech.edu.in
[20] Richard E. Nisbett, Joshua Aronson and Clancy Blair, William Dickens,
James Flynn, Diane F. Halprn, Eric Turkheimer, “Intelligence - New
Findings and Theoretical Developments,” American Psychologist, vol.
67, pp. 130-159, 2012. doi: 10.1037/a0026699
[21] McEwen, B. S, “The neurobiology of stress: From serendipity to clinical
relevance,” Brain Research, vol. 886, pp. 172–189, 2000.
doi:10.1016/S0006- 8993(00)02950-4.
@article{"International Journal of Medical, Medicine and Health Sciences:70307", author = "Lakshmi Dhandabani and Rajeev Sukumaran", title = "Correlational Analysis between Brain Dominances and Multiple Intelligences", abstract = "Aim of this research study is to investigate and
establish the characteristics of brain dominances (BD) and multiple
intelligences (MI). This experimentation has been conducted for the
sample size of 552 undergraduate computer-engineering students. In
addition, mathematical formulation has been established to exhibit
the relation between thinking and intelligence, and its correlation has
been analyzed. Correlation analysis has been statistically measured
using Pearson’s coefficient. Analysis of the results proves that there
is a strong relational existence between thinking and intelligence.
This research is carried to improve the didactic methods in
engineering learning and also to improve e-learning strategies.", keywords = "Thinking style assessment, correlational analysis,
mathematical model, data analysis, dynamic equilibrium.", volume = "9", number = "2", pages = "217-5", }
