Diagnostics of the Student’s Learning Style With the Use of Modern Information Technologies

The paper deals with learning styles and their initial diagnostics in the process of the student’s learning. It is focused on a method of learning styles recognition with the support of modern information technologies. The paper analyses different methods of the learning styles diagnostics, incorporating this issue into the scientific field of artificial intelligence and presents an idea on how to diagnose a learning style by using an unconventional fuzzy logic linguistic expert system. The expert system was designed to diagnose learning styles of university students in adaptive computer aided learning systems. A significant benefit is continuous numerical evaluation of the student’s degree of affiliation to all learning categories (types of student) with a possibility of simple determination of dominant and subdominant types, the use of a linguistic rule-based decision-making model, which is completely transparent and open, and the use of a decision-making procedure corresponding to the process of human consideration. The paper is an example of an application of modern information technologies in education.

REFERENCES:

• Brusilovskv, P. (2001). Adaptive hypermedia. In User Modeling and User Adapted Interaction. 77(1-2), Publisher: Springer, 84-129, ISSN09241868.
• Brusilovsky, P. (2003). From Adaptive Hypermedia to the Adaptive Web. Mench & Computer. Interaktion in Bewegung. Stuttgart: B. G. Teubner, 21-24. ISSN 0001-0782.
• Bureš, M, & Jelínek, I. (2004). Adaptivní webové systémy v e-leamingu. In Belcom‘04. Praha: ČVUT, 223-226. ISBN 80-01-02923-9.
• Carver, C.A., Howard, R.A., & Lane, W.D. (1999). Addressing different learning styles through course hypermedia. IEEE Transactions on Education, 42,33-38, ISSN 0018-9359.
• Coffield, F. (2004). Learning styles and pedagogy in post-16 learning. In A systematic and critical review. London: Leming and skills research centre. ISBN 1-85338-918-8.
• Čáp, J. (1993).Psychologie výchovy a vyučování. Praha: Karolinum. ISBN 80-7066- 534-3.
• Felder, R.M., & Silverman, L.K. (1998). Learning and Teaching Styles in Engineering Education. In Journal of engineering education, 78 (7). 674-681. ISSN 2168-9830
• Felder, R.M., & Soloman, B.A. (2004). Index of Learning Styles. Retrieved 5/06/2013. from http://www.ncsu.edu/felder-public/ILSpage.html.
• Felder, R ML, & Spurlin, J. (2005). Applications, Reliability and Validity of the Index of Learning Styles. International Journal of Engineering Education, 21 (1), 102-112. ISSN 0949-149X.
• Kaliská, L. (2012). Felder’s Learning Style Concept and its Index of Learning Style Questionnaire in the Slovak Conditions. GRANTjoumal. 1,(1). Retrieved 3/08/2013, from: http://.www.grantjournal.com issue 0101 PDF 0101.pdf.
• Kolb, D.A. (1984). Experiential learning: Experience as the source of learning and development. Englewood Cliffs, New Jersey: Prentice Hall.
• Kostolányová, K. (2012). Teorie adaptivního e-leamingu. Ostravská univerzita: Ostrava. ISBN: 978-80-7464-014-8.
• Kulič, V. (1992). Psychologie řízeného učení. Praha:Academia. ISBN 80-200-0447-5
• Liu, H. (2010). Pedagogical Strategy Model in Adaptive Learning System Focusing on Learning Styles. Entertainment for Eduacation. Digital Techniques and Systems. Lecture Notes in Computer Science. Spring-Verlag Berlin: Heidelberg. 156-164, ISBN 978-3-642-14532-2.
• Mareš, J. (1998). Styly učeni žáků a studentů. Praha: Portál. ISBN 80-7178-246-7.
• Marton, F. (1988). Describing and improving learning. In R. Schmeck (Ed), Learning Strategies and Learning Styles. New York: Plenum Press, 53–82.
• MaRik, V. (1997). Umělá inteligence (2), Praha: Academia. ISBN 80-200-0504-8
• Myers, I, & Briggs, K. (1998). MBTI. Retrieved 03/05/2013, from http://www. myersbriggs.org/my-mbti-personality-type/mbtibasics.
• Nakonečný, M(1998) Základy psychologie. Praha: Academia. ISBN 80-200-0689-3.
• NovAk, V. (2000). Základy fuzzy modelování. BEN Praha:. ISBN 80-7300-009-1.
• Paramythis, A. & Loidl-Reisinger, S. (2004). Adaptive Learning Environments and e-Leaming Standards. In Electronic Journal of E-learning. 2(2).
• Pokorný M. (2012). Expertní systémy. Ostrava: Ostravská univerzita v Ostravě.
• Průcha, J. Walterova, E. & Mareš, J.(2009). Pedagogický slovník. Praha: Portál. ISBN 978-80-7363-647-6.