Mobile devices use in analyzing the engineering students attitude towards programming by using a fuzzy logic technique

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, t...

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Bibliographic Details
Published in:Computer applications in engineering education Vol. 29; no. 3; pp. 538 - 549
Main Authors: Ozdemir, Ali, Balbal, Kadriye Filiz, Senel, Berat Can
Format: Journal Article
Language:English
Published: Hoboken Wiley Subscription Services, Inc 01.05.2021
Subjects:
Applications programs
attitude determination
Attitudes
Electronic devices
Engineering
Engineering education
Fuzzy logic
Learning
Mobile computing
mobile devices
mobile learning
Programming
Reliability analysis
Software engineering
Statistical methods
Students
Variance analysis
ISSN:1061-3773, 1099-0542
Online Access:Get full text
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Summary: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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ISSN:1061-3773
1099-0542
DOI:10.1002/cae.22200