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Classification, Clustering and Association Rule Mining in Educational Datasets Using Data Mining Tools: A Case Study

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Cybernetics and Algorithms in Intelligent Systems (CSOC2018 2018)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 765))

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Abstract

Educational Data Mining is an emerging field in the data mining domain. In this competitive world scenario, the quality of education needs to improve. Unfortunately most of the students’ data are becoming data tombs for not analyzing the hidden knowledge. The educational data mining tries to uncover the hidden knowledge by discovering relationships between student learning characteristics and behavior. With this educational data modeling, the educators may plan for future learning pedagogy to support the student’s learning style. This knowledge may be applied by the academic planners to improve the quality of education and decrease the failure rate. In this paper, we had collected real dataset containing 666 instances with 11 attributes. The data is from the Common Entrance Examination (CEE) data of a particular year for admission to medical colleges of Assam, India conducted by Dibrugarh University. We tried to find out the association rules using the data. Various clustering and classification methods were also used to compare the suitable one for the dataset. The data mining tools applied in the educational data were Orange, Weka and R Studio.

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Author information

Authors and Affiliations

  1. Dibrugarh University, Assam, India

    Sadiq Hussain

  2. Faculty of Computer Science and IT, University of Malaya, Kuala Lumpur, Malaysia

    Rasha Atallah

  3. Department of Computer System and Technology, University of Malaya, Kuala Lumpur, Malaysia

    Amirrudin Kamsin

  4. Department of Statistics, Dibrugarh University, Assam, India

    Jiten Hazarika

Authors
  1. Sadiq Hussain
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  2. Rasha Atallah
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  3. Amirrudin Kamsin
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  4. Jiten Hazarika
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Corresponding author

Correspondence to Sadiq Hussain .

Editor information

Editors and Affiliations

  1. Faculty of Applied Informatics, Tomas Bata University in ZlĂ­n, ZlĂ­n, Czech Republic

    Radek Silhavy

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Hussain, S., Atallah, R., Kamsin, A., Hazarika, J. (2019). Classification, Clustering and Association Rule Mining in Educational Datasets Using Data Mining Tools: A Case Study. In: Silhavy, R. (eds) Cybernetics and Algorithms in Intelligent Systems . CSOC2018 2018. Advances in Intelligent Systems and Computing, vol 765. Springer, Cham. https://doi.org/10.1007/978-3-319-91192-2_21

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