Analysis and Prediction of Student’s Academic Performance in University Courses

نویسندگان

  • Garima Sharma
  • Gyan Ganga
  • Santosh K. Vishwakarma
چکیده

Management of huge amount of data has always been a matter of concern. With the increase in awareness towards education, the amount of data in educational institutes is also increasing. The increasing growth of educational databases, have given rise to a new field of data mining, known as Educational Data Mining (EDM). With the help of this one can predict the academic performance of a student that can help the students, their instructors and also their guardians to take necessary actions beforehand to improve the future performance of a student. This paper deals with the implementation of ID3 decision tree algorithm to build a predictive model based on the previous performances of a student. The dataset used in this paper is the semester data of the students of a private institute of India. Rapidminer, an open source software platform is used to obtain the results. General Terms Data mining, Knowledge Discovery in Databases, Classification, ID3 induction algorithm, Performance prediction

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تاریخ انتشار 2017