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


Ozdemir A., Balbal K. F., Senel B. C.

COMPUTER APPLICATIONS IN ENGINEERING EDUCATION, cilt.29, sa.3, ss.538-549, 2021 (SCI-Expanded) identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 29 Sayı: 3
  • Basım Tarihi: 2021
  • Doi Numarası: 10.1002/cae.22200
  • Dergi Adı: COMPUTER APPLICATIONS IN ENGINEERING EDUCATION
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, Computer & Applied Sciences, EBSCO Education Source, INSPEC, Metadex, DIALNET, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.538-549
  • Anahtar Kelimeler: attitude determination, fuzzy logic, mobile devices, mobile learning
  • Dokuz Eylül Üniversitesi Adresli: Hayır

Özet

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.