A Design of Android Based Mobile Application for Determination of Learning Style

Abstract

In this study an android based mobile application is designed for determining Learning Styles of the individuals. Easy, rapid and efficient learning is very important for each individual that affects their success in business and daily life. As long as life-long learning continues, the importance of recognizing the individuals learning abilities becomes more important. The aim of this study is to make individuals be aware of their abilities on the way of easy learning by using the proposed mobile application which can be executed on Android based mobile devices. As the technology evolves, the use of mobile devices has become inevitable. Most of the individuals use smart phones for many different aims such as communication, entertainment and learning. Hence commonly usage of mobile devices makes the proposed system more practical. By simply downloading the proposed application to the mobile device, individuals will be able to run the program. The proposed sytem is designed and developed by usig Java Android programming.

Keywords

• Learning style,Mobile application

References

1. Z. Ghazivakili, R. N. Nia, F. Panahi, M. Karimi, H. Gholsorkhi, and Z. Ahmadi, The role of critical thinking skills and learning styles of university students in their academic performance, J Adv Med Educ Prof 2 (2014), 95–102. E. €Ultanır, Y. G. €Ultanır, and G. €O. Temel, The examination of university students’ learning styles by means of Felder-Silverman index, Educ Sci 37 (2012), 29–42. Y. Liu and D. Ginther, Cognitive styles and distance education. Online Journal of Distance Learning Administration, Volume II, Number III, Fall 1999 State University of West Georgia, Distance Education. K. Logan and P. Thomas, Learning Styles in Distance Education Students Learning to Program. 14th Workshop of the Psychology of Programming Interest Group, Brunel University, June 2002 www.ppig.org K. Sabry and L. Baldwin, Web-based learning interaction and learning styles, Brit J Educ Technol 34 (2003), 443–454. A. Nikolaou and M. Koutsouba, Incorporating 4MAT model in distance instructional material—An innovative design, Eur J Open Dist E-Learning 16 (2012), 50–63. A. Susan, Influence of Learning Styles and Personality on Distance Learning, Santo University of South Dakota, Vermillion, SD, USA, TCC 2005, Online Conference. T. C. DeBello, Comparison of eleven major learning styles; variables, appropriate populations, validity of instrumentation and the research behind them. J Read Writ Learn Disabil Int 6 (1990), 203–222. A. Ozdemir, A. Alaybeyoglu, N. Mulayim, K.F. Balbal, Performance Evaluation of Learning Styles Based on Fuzzy Logic Inference System, Computer Applications in Engineering Education, pp:853-865. A. Ozdemir, A. Alaybeyoglu, K.F. Balbal, Learning Style Determination with Gregorc Learning Style Model: Example for Faculty of Engineering, ICRES 2017. K.F. Balbal, N. Mulayim, A. Ozdemir, A. Alaybeyoglu, Fuzzy Logic Based McCarthy Learning Style Inference System, ICRES 2016.