Programming learning style recommendation using fuzzy logic / Nur Fadhilah Ain Susen

• Main Author: Susen, Nur Fadhilah Ain
• Format: Thesis
• Language: English
• Published: 2017
• Subjects: Instruments and machines; Electronic Computers. Computer Science; Programming. Rule-based programming. Backtrack programming; Computer software; Application program interfaces; Application software; Development. UML (Computer science); Integrated software; Fuzzy logic
• Online Access: https://ir.uitm.edu.my/id/eprint/69414/1/69414.pdf; https://ir.uitm.edu.my/id/eprint/69414/

Programming subjects are fundamental to Computer Science students as students need to comprehend these subjects in order to be a good computer scientist. It is also one of the important and core subject for Computer Science students. Programming subject also complex to implement if students do not have any basic. This may cause the understanding about programming become hard and difficult. While, techniques of study for each person are different based on their personality. To solve the problem a recommendation system using fuzzy logic is proposed on Myers-Briggs Type Indicator (MBTI). MBTI model is a personality test used to suggest study techniques that suitable for student so they can learn programming subjects more effectively. Methodology used consists of collection of data about programming and MBTI, design the interface, process of implementation and evaluation of the prototype. A conceptual framework is developed based on fuzzy logic system technique and Myers-Briggs Type Indicator (MBTI). MBTI result will be used as a feeder to fuzzy logic engine. The prototype can help students to choose appropriate learning style for programming. The prototype is evaluated using accuracy testing which is measure the accurate value of the exactly output. The result testing for this prototype is 36.36%. For the future works combination of the other model of learning style and techniques of programming will be added to improve the accuracy of the result.