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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/1873
Title: Applying data mining methodology to identify student dropout causes
Authors: Mai Nguyen Vy 
Keywords: Data mining;Dropout student
Issue Date: 2024
Abstract: 
Studying dropout in higher education has become of greater importance in recent years. Many research projects have been conducted on examining, predicting, alleviating the situation. This thesis aims to predict causes of dropping out of university through the use of machine learning models. The data used in this paper were obtained in two ways: sending a survey to students of VGU and a dataset from an external source. The data analysis process on survey data revealed an interesting connection between the practicality of lectures and how interesting they are, as far as students were concerned. Running ML models on the external dataset showed that grades and curricular units played an important role in distinguishing a dropout student. Based on those results, further discussion was made, followed by laying out existing shortcomings of the paper, which can be improved in future works.
URI(1): https://epub.vgu.edu.vn/handle/dlibvgu/1873
Rights: Attribution-NonCommercial 4.0 International
Appears in Collections:Computer Science (CS)

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