Developing a Fuzzy Intelligent Learning System to Improve Mobile App Development Skills for Computer Teacher Students

Document Type : Research papers review in the scientific journal

Authors

1 Education technology, faculty of education, Mansoura university, Egypt

2 mansours university

Abstract

The rapid evolution of mobile technology has necessitated the integration of innovative teaching methods into computer education. This paper presents a fuzzy intelligent learning system (FILS) to improve mobile app development skills for computer teacher students. The proposed methodology uses a self-learning system based on fuzzy logic from data that represents learners' knowledge and skill capabilities and their educational requirements. FILS is used to improve knowledge delivery based on individual learners' characteristics as it adapts during the learning situation and content delivery. A total of 70 students were randomly assigned to either a control group or an experimental group, with each group consisting of 35 students. The control group received traditional instruction methods, while the experimental group engaged with the proposed fuzzy intelligent learning system. The methodology embraced a quasi-experimental design, focusing on comparative analysis between the pre-test and post-test results of both groups. The FILS was tailored to adjust the learning content dynamically based on the fuzzy logic inference system, which considered individual learning pace and understanding levels. Results indicated a significant improvement in mobile app development skills within the experimental group compared to the control group. Statistical analysis showed that the experimental group’s post-test scores were significantly higher, suggesting that the FILS effectively facilitated a deeper understanding and proficiency in mobile app development.

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