The algorithm of mathematical modelling for learning styles of pre-school children

ABSTRACT This study examines pre-school children's learning styles by utilising a mathematical model. The model uses a Euclidean geometry algorithm to generate a graphical representation of the learning styles. The algorithm of the developed mathematical model was developed as a practical application of the theoretical assumptions. Index of Learning Styles for Children (ILSC), developed by one of the researchers, has been applied to a total of 301 five-year-old children. Results of the study indicate that children utilise the active, cognitive and visual learning styles under the control of the right hemisphere, and the sequential (analytical) learning styles under the control of the left hemisphere. The modelling algorithm reveals that the children's learning style preferences are shifted towards the right hemisphere at the rate of 8%. The results also provide empirical support that the developed model can mathematically explain the theoretical assumptions it is based on.

[1]  Lynne Celli Sarasin.  Learning Style Perspectives: Impact in the Classroom , 1998 .

[2]  R. Felder,et al.  Understanding Student Differences , 2005 .

[3]  David F. Treagust,et al.  Students' understanding of the role of scientific models in learning science , 2002 .

[4]  M. Zywno.  A Contribution to Validation of Score Meaning for Felder- Soloman's Index of Learning Styles , 2003 .

[5]  I. B. Myers.  Manual: A Guide to the Development and Use of the Myers-Briggs Type Indicator , 1985 .

[6]  Christopher Haines,et al.  Recognizing constructs within mathematical modelling , 2001 .

[7]  A. Reiss,et al.  Brain development, gender and IQ in children. A volumetric imaging study. , 1996, Brain : a journal of neurology.

[8]  K. Dunn,et al.  Teaching Elementary Students Through Their Individual Learning Styles: Practical Approaches for Grades 3-6 , 1978 .

[10]  Kenneth Dunn,et al.  The Complete Guide to the Learning Styles Inservice System , 1998 .

[11]  Mildred C. Robeck,et al.  Psychological Foundations of Learning and Teaching , 1969 .

[12]  D. Kolb,et al.  Learning Styles and Learning Spaces: Enhancing Experiential Learning in Higher Education , 2005 .

[13]  Cerebral Hemispheres and Learning: A Study of the Correlation between Brain Dominations and Learning Styles , 2011 .

[14]  F. Coffield.  Should We Be Using Learning Styles? What Research Has to Say to Practice , 2004 .

[15]  Lieven Verschaffel,et al.  Everyday Knowledge and Mathematical Modeling of School Word Problems , 2002 .

[16]  Thomas F. Hawk,et al.  Using Learning Style Instruments to Enhance Student Learning , 2007 .

[17]  R. Dunn,et al.  Survey of research on learning styles , 1989 .

[18]  Richard M. Felder,et al.  MATTERS OF STYLE , 2004 .

[19]  Michael C. Corballis,et al.  Left Brain, Right Brain: Facts and Fantasies , 2014, PLoS biology.

[20]  J. Iaccino,et al.  Left Brain - Right Brain Differences: Inquiries, Evidence, and New Approaches , 1993 .

[21]  Sang Ha Lee,et al.  A Study of the Reliability and Validity of the Felder-Soloman Index of Learning Styles © , 2005 .

[22]  R. Felder,et al.  Learning and Teaching Styles in Engineering Education. , 1988 .

[23]  Sofia B. Dias,et al.  FuzzyQoI model: A fuzzy logic-based modelling of users' quality of interaction with a learning management system under blended learning , 2013, Comput. Educ..

[24]  C. Lebel,et al.  Longitudinal Development of Human Brain Wiring Continues from Childhood into Adulthood , 2011, The Journal of Neuroscience.

[25]  I. Jambaqué,et al.  The right brain hemisphere is dominant in human infants. , 1997, Brain : a journal of neurology.

[26]  Jehanzeb R. Cheema,et al.  Predicting high school student use of learning strategies: the role of preferred learning styles and classroom climate , 2016 .

[27]  R. Lambert,et al.  Myths or Misnomers: Research-based Realities in the Classroom Literature Review for Deans for Impact (2015) , 2017 .

[28]  Tanbhir Hoq,et al.  Micro hydro power: promising solution for off-grid renewable energy source , 2011 .

[29]  D. Myers,et al.  Thinking About Psychology: The Science of Mind and Behavior , 2003 .

[30]  B. Joyce,et al.  Models of Teaching , 2024 .

[31]  Wayne Rimmer.  Teaching with style , 2009 .

[32]  J. Biggs.  Individual differences in study processes and the Quality of Learning Outcomes , 1979 .

[33]  Norman E. Wallen,et al.  How to Design and Evaluate Research in Education , 1990 .

[34]  L JEGATHA DEBORAH,et al.  Fuzzy-logic based learning style prediction in e-learning using web interface information , 2015, Sadhana.

[35]  J. Healy.  Your child's growing mind : brain development and learning from birth to adolescence , 2004 .

[36]  B. J. Casey,et al.  Quantitative magnetic resonance imaging of human brain development: ages 4-18. , 1996, Cerebral cortex.

[37]  J. P. Das,et al.  Simultaneous-Successive Processing and Planning , 1988 .

[38]  Jeffery E. Olson,et al.  A Meta-Analytic Validation of the Dunn and Dunn Model of Learning-Style Preferences , 1995 .

[39]  Robert Loo,et al.  A Meta-Analytic Examination of Kolb's Learning Style Preferences Among Business Majors , 2002 .

[40]  Allan G. Harrison,et al.  How do Teachers and Textbook Writers Model Scientific Ideas for Students? , 2001 .

[41]  Richard Lehrer,et al.  A Developmental Approach for Supporting the Epistemology of Modeling , 2007 .

[42]  Antonio F. Gómez-Skarmeta,et al.  An adaptive learning fuzzy logic system for indoor localisation using Wi-Fi in Ambient Intelligent Environments , 2012, 2012 IEEE International Conference on Fuzzy Systems.

[43]  L. Curry.  Cognitive and learning styles in medical education. , 1999, Academic medicine : journal of the Association of American Medical Colleges.

[44]  John K. Gilbert,et al.  Models and Modelling: Routes to More Authentic Science Education , 2004 .

[45]  T. C. Bello.  COMPARISON OF ELEVEN MAJOR LEARNING STYLES MODELS: VARIABLES, APPROPRIATE POPULATIONS, VALIDITY OF INSTRUMENTATION, AND THE RESEARCH BEHIND THEM , 1990 .

[46]  Shyi-Ming Chen,et al.  Weighted Fuzzy Rule Interpolation Based on GA-Based Weight-Learning Techniques , 2011, IEEE Transactions on Fuzzy Systems.

[47]  Francis L. Bacon,et al.  National Association of Secondary-School Principals , 1942 .

[48]  D. Kolb.  Experiential Learning: Experience as the Source of Learning and Development , 1983 .

[49]  Louise Anne McLean,et al.  Cognitive style and gender differences in children’s mathematics achievement , 2013 .

[50]  A. Miyake,et al.  The Nature and Organization of Individual Differences in Executive Functions , 2012, Current directions in psychological science.

[51]  Sanghee Yeo.  Handbook of individual differences, learning, and instruction. , 2010, Korean journal of medical education.

[52]  Nian-Shing Chen,et al.  Effects of teaching and learning styles on students' reflection levels for ubiquitous learning , 2011, Comput. Educ..

[53]  Marilla D. Svinicki,et al.  Attempted Validation of the Scores of the VARK: Learning Styles Inventory With Multitrait–Multimethod Confirmatory Factor Analysis Models , 2010 .

[54]  Richard Lesh,et al.  Foundations of a Models and Modeling Perspective on Mathematics Teaching, Learning, and Problem Solving , 2003 .

[55]  Mauro Maldonato,et al.  The creative brain , 2014, 2014 5th IEEE Conference on Cognitive Infocommunications (CogInfoCom).