Exploring the High Potential Factors that Affects Students’ Academic Performance: A Recent Study Approach

Abstract

The rapid growth of the student population has resulted the expansion of educational facilities at all levels. Teachers now have a plethora of responsibilities. It is the responsibility of teachers to guide students in choosing a career path based on their abilities and aptitudes. The field of Data Mining mines educational data from large amounts of data in order to improve the quality of educational processes. Today's educational system needs to develop individuals' problem-solving and decision-making skills, as well as their social skills. Educational Data Mining is one of the Data Mining applications used to uncover hidden patterns and knowledge in educational institutions. Fast learners, average learners, and slow learners have been identified as three important groups of students. In fact, students are likely to struggle in a variety of ways. The main objective of this research work is to enhance the students’ academic performance prediction by identifying the significant features through the attribute selection method. This work focuses on finding the high potential factors that affects the performance of college students. This finding will improve the students’ academic performance positively.