An inclusive survey of students performance with various data mining methods

  • Authors

    • A S. Arunachalam
    • K Rajeswari
    2018-06-08
    https://doi.org/10.14419/ijet.v7i2.33.14825
  • Educational Data Mining, Students Performance, Patterns, Classification

  • Abstract

    Educational institutions are the source of generating quality students in order to make them do better service for the nation. It is a must for all educational institutions to be aware of the competency and academic level of every student so as to study their performance. The key attributes to identify the performance are to have controlled parameter with clear data. So it is important to set the standards and calibration measures in order to make the study of students’ performance an efficient one. There are several tools and techniques available to perform this prediction study. Among all, Data mining is the best and the most efficient technique to handle prediction process. Among data mining, EDM (Educational Data Mining) is much more popular in the present century and hence it is beneficial to make a research on the current technique. This survey paper focuses on various Data Mining approaches in order to forecast student’s performance and bring clarity in students’ results and faculty’s contribution as a success.

     

     

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  • How to Cite

    S. Arunachalam, A., & Rajeswari, K. (2018). An inclusive survey of students performance with various data mining methods. International Journal of Engineering & Technology, 7(2.33), 522-525. https://doi.org/10.14419/ijet.v7i2.33.14825

    Received date: 2018-06-30

    Accepted date: 2018-06-30

    Published date: 2018-06-08