Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

Educational Data Mining for Classification of Students according to their Performance

Author : Amruta Joshi 1 Prof. A. Thomas 2

Date of Publication :7th February 2017

Abstract: Educational Data Mining is the Data Mining technique that is used to describe a research discipline that uses data collected or gathered from educational areas such as universities and colleges in research that helps to develop a method to gain information or knowledge from the data which we can use to further understand the relationship and environment between student and college or university. Every student lacks at some areas in academic and other performance. As sometimes student don’t understand where they are lacking because of which they cannot improve their performance which leads to their poor performance in final results. So there is a need of one system which can help the teachers and students to understand student’s performance level. With the help of this system, Teachers will identify the student’s performance level i.e. which student is good in academics which student is weak and can focus more on the weaker students and can take corrective steps from the initial stage to get better result in final exams.

Reference :

    1. Norlida Buniyamin, Usamah bin Mat, Pauziah Mohd Arshad : “Educational Data Mining for Prediction and Classification of Engineering Students Achievement,” 2015 IEEE 7th International Conference on Engineering Education (ICEED).
    2. Bo Guo∗, Rui Zhang†, Guang Xu‡, Chuangming Shi§ and Li Yang§ “Predicting Students Performance in Educational Data Mining.”: 2015 IEEE International Symposium on Educational Technology
    3. Karan Sukhija* Dr. Manish Jindal Dr. Naveen Aggarwal “The Recent State of Educational Data Mining: A Survey and Future Visions.” : 2015 IEEE 3rd International Conference on MOOCs, Innovation and Technology in Education (MITE).
    4. Alana M. de Morais and Joseana M. F. R. Araújo Evandro B. Costa “Monitoring Student Performance Using Data Clustering and Predictive Modelling.”: IEEE , 2014.
    5. Shaleena K.P, Shaiju Paul “Data Mining Techniques for Predicting Student Performance.” 2015 IEEE International Conference on Engineering and Technology (ICETECH), 20th March 2015, Coimbatore, TN, India
    6. Krina Parmar Prof. Dineshkumar Vaghela Dr Priyanka Sharma “Performance prediction of students using distributed Data Mining.” 2015 IEEE Sponsored 2nd International Conference on Innovations in Information Embedded and Communication Systems (ICIIECS)

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