Suitable Personality Traits for Learning Programming Subjects: A Rough-Fuzzy Model
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...
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| Published in: | International journal of advanced computer science & applications Vol. 8; no. 8 |
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| Main Authors: | , , , , , , |
| Format: | Journal Article |
| Language: | English |
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West Yorkshire
Science and Information (SAI) Organization Limited
01.01.2017
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| ISSN: | 2158-107X, 2156-5570 |
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| Abstract | 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. |
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| AbstractList | 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. |
| Author | Hilmi, Mohd Abdul, Izzatdin Uddin, Qamar Jaafar, Jafreezal Omar, Mazni Rehman, Abdul Basri, Shuib |
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| SubjectTerms | Algorithms Cognition & reasoning Colleges & universities Composition Decision theory Fuzzy logic Fuzzy set theory Fuzzy sets Learning Object oriented programming Personality Personality traits Set theory Structured programming |
| Title | Suitable Personality Traits for Learning Programming Subjects: A Rough-Fuzzy Model |
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