期刊名称：International Journal of Advanced Computer Science and Applications(IJACSA)
印刷版ISSN：2158-107X
电子版ISSN：2156-5570
出版年度：2017
卷号：8
期号：8
DOI：10.14569/IJACSA.2017.080820
出版社：Science and Information Society (SAI)
摘要：Programming is a cognitive activity which requires logical reasoning to code for abstract presentation. This study aims to find out the personality traits of students who maintain the effective grades in learning programming courses such as structured programming (SP) and object oriented programming (OOP) by gender classification. Data were collected from three universities to develop, validate, and generalize the Rough-Fuzzy model. Genetic and Johnson algorithms were applied under Rough set theory’s (RST) principles to extract the decision rules. In addition, Standard Voting, Naïve Bayesian, and Object Tracking procedures were applied on the generated decision rules to find the prediction accuracy of each algorithm. Mamdani’s Fuzzy Inference System (FIS) was used for mapping the decision rules’ condition (input) to decision (output) based on fuzzy set theory (FST) to develop the model. The results highlighted that certain personality compositions can be suitable for scoring good grades in programming subjects. For instance, a female student is capable enough to improve the programming skills if she is composed of introvert and sensing personality traits. Therefore, it is important to investigate an appropriate personality composition for programming learners.
