Fuzzy Logic based Personalized Learning Navigator for Students

Abstract

The student performance tracking system using fuzzy logic algorithm is designed to transform online education by addressing the challenges students face in personalized guidance, study scheduling and resource navigation. The objective of this project is to categorize students' marks as good, average, or bad, helping them understand their performance level in each subject. Using fuzzy logic, the marks of the students are categorized by comparing them with predefined membership functions and ranges for each category. Fuzzy logic provides an accurate evaluation of marks compared to manual categorization, considering various degrees of membership rather than fixed thresholds. This approach ensures a precise assessment of students' performance, providing the benefits of automated categorization over traditional manual methods. With the categorized marks the schedule is provided for each subject based on the range they have scored i.e., good, average, or bad providing with improvement in performance evaluation. Additionally, the student can get access to the online platforms offering free course materials relevant to each subject with just one click. It helps the students to track their progress, maintain a personalized timetable for learning and access the free courses in the same place.