Browsing by Author "Balbal, KF"

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    Performance Evaluation of Learning Styles Based on Fuzzy Logic Inference System
    Ozdemir, A; Alaybeyoglu, A; Mulayim, N; Balbal, KF
    Determining best convenient learning style in accordance with the individual's capabilities and personalities is very important for learning rapidly, easily, and in high quality. When it is thought that each individual has different personality and ability, it can be recognized that each individual's best convenient learning style will be different. Because of the importance of lifelong learning, many methods and approaches have been developed to determine learning styles of the individuals. In this study, a rule based fuzzy logic inference system is developed to determine best convenient learning styles of the engineering faculty stuffs and the students. During studies, two different learning style models namely Honey&Mumford and McCarthy are used in implementations. This study is carried out with a total number of 60 and 26 engineering faculty students and stuffs, respectively. The personal information form and Learning Style Preference Survey of Honey&Mumford and McCarthy are used to collect the data which are analyzed using the techniques of frequency, percentage, mean, standard deviation, and t-test. While Honey&Mumford learning style classifies engineering faculty students and stuffs as Activist, Reflector, Theorist, and Pragmatist; McCarthy learning style classifies them as Innovative, Analytic, Common Sense, and Dynamic. Gender, age, and department are selected as the metrics for evaluation of the system performance. (C) 2016 Wiley Periodicals, Inc
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    Mobile devices use in analyzing the engineering students attitude towards programming by using a fuzzy logic technique
    Ozdemir, A; Balbal, KF; Senel, BC
    The aim of this study is to use mobile devices in the determination of engineering students' attitudes towards programming by using a fuzzy logic technique. First of all, a mobile game that is played by engineering students is developed to make learning programming more enjoyable. After that, the proposed fuzzy logic-based attitude determination system which runs on mobile devices comes into play. Student answers and gives points between 1 and 5 to the survey questions which are presented by the developed mobile application. These points are first evaluated in the fuzzification step by using membership functions and then the fuzzied input is given to the rule base step. To get crisp output value, fuzzied output is defuzzified at the last step of the fuzzy logic-based system. Hence the attitude of the student towards programming is inferenced. The developed system is carried out with 100 first-grade students of the software engineering department. Frequency, mean, standard deviation, normality, t test, and analysis of variance (ANOVA) analyses are performed with the obtained data. Results show that the proposed fuzzy logic-based system performs much better than the classical approach. As a result of Article Reliability Analysis of the Attitude Scale Towards Mobile Learning, the scale is found highly reliable. A significant difference is found in favor of fuzzy logic-based attitude score among classical logic-based attitude scores as a result of the paired-samples t test. The results of t test and ANOVA tests according to gender, mother, and father education levels are found not statistically significant.
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    Fuzzy logic based performance analysis of educational mobile game for engineering students
    Ozdemir, A; Balbal, KF
    The aim of this study is to examine the effect of an educational android mobile game on the attitude of engineering students. For this purpose, an educational mobile game is developed and a fuzzy logic based attitude determination system is modeled. The study is carried out with 30 students of mechatronic engineering. A mobile game which is called Select Box-Solve Question has been developed in the android studio environment. Besides this; to analyse the performance of the game on the success of education, a fuzzy logic-based attitude determination system, which consists of four number of inputs and outputs, is modeled. These input and output values constitute the factors of the attitude scale. The Triangular Membership Function is used as the Fuzzification step of the Fuzzy Logic Technique. Four different defuzzification methods are used and the results of these methods are compared and analysed.