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Exploring the High Potential Factors that Affects Students’ Academic Performance: A Recent Study Approach | Chapter 01 | Novel Perspectives of Engineering Research Vol. 8

 Because of the increasing growth of the student population, educational facilities at all levels have been expanded. Teachers are now tasked with a multiplicity of duties. Teachers are responsible for guiding pupils in choosing a career path based on their strengths and aptitudes. Data Mining is the method of extracting educational data from enormous amounts of data in order to improve the quality of educational activities. Individuals' problem-solving and decision-making skills, as well as their social skills, must be developed in today's educational system. Educational Data Mining is one of the Data Mining applications used in educational institutions to find hidden patterns and information. Three key student groups have been identified: fast learners, average learners, and slow learners. In fact, students are likely to have difficulties in a variety of ways. The primary goal of this research is to improve the prediction of students' academic performance by finding significant traits using the attribute selection approach. This research focuses on identifying high-potential elements that influence college students' success. This discovery will have a favourable impact on the students' academic achievement.


Author(S) Details

R. Kaviyarasi
Principal, Sri Vidya Mandir Arts & Science College (A), Uthangarai, Krishnagiri (Dt)- 636902 Tamilnadu, India.

T. Balasubramanian
Principal, Sri Vidya Mandir Arts & Science College (A), Uthangarai, Krishnagiri (Dt)- 636902 Tamilnadu, India.

View Book:- https://stm.bookpi.org/NPER-V8/article/view/6107

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