Abstract
Recent years have revealed an increasing attention and interest in various countries about the problem of dropout of the students in the school and to find out its chief contributing factors. In our model, we attempt to demonstrate how a specific factor can affect students’ academic life, which subsequently produces dropout among school students. In this paper, we propose a methodology and a specific clustering algorithm to identify the factors that results in dropout among the students at different educational levels, such as primary, secondary, and higher secondary and also their percentage of impact among the students. This research will guide the teachers and school administration to improve this dropout scenario of their school. A solution to this problem can be resolved with the use of educational data mining (EDM).
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Maheshwari, E., Roy, C., Pandey, M., Rautray, S.S. (2020). Prediction of Factors Associated with the Dropout Rates of Primary to High School Students in India Using Data Mining Tools. In: Satapathy, S., Bhateja, V., Nguyen, B., Nguyen, N., Le, DN. (eds) Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 1013. Springer, Singapore. https://doi.org/10.1007/978-981-32-9186-7_26
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DOI: https://doi.org/10.1007/978-981-32-9186-7_26
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