University Dropout Prevention through the Application of Big Data
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Abstract
This study explores the reasons for the suspension and dropout of full-time university students at a university in Taiwan and suggests better timing and strategies for student counseling. In this study, the narrative statistical analysis is used to analyze and discuss the sample objects, and then use data mining technology to find characteristic phenomena and classification conditions of the students who are suspended or dropout. Other studies related to dropouts rarely use leading indicators to predict the student dropout probability in real-time, most likely because of the timeliness and availability of student data. Therefore, this study proposes to use daily changes in absence indicators as predictive variables. Through the use of discriminant analysis to construct discriminant functions, the coefficient value of each student's withdrawal from university and early warning threshold for determining withdrawal from university can be presented in real-time in order to effectively provide the student with immediate counseling.
References
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Dynarski, M.; Gleason, P. How Can We Help? What We Have Learned From Recent Federal Dropout Prevention Evaluations. J. Educ. Stud. Placed Risk (JESPAR) 2002, 7, 43--69.
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Knowles, J.E. Of needles and haystacks: Building an accurate statewide dropout early warning system in Wisconsin. JEDM J. Educ. Data Min. 2015, 7, 18--67.
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Lamb, S.; Rice, S. Effective Strategies to Increase School Completion Report: Report to the Victorian Department of Education and Early Childhood Development; Communications Division, Department of Education and Early Childhood Development: Melbourne, Australia, 2008.
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Wang Jianhua 2004. Application of data mining technology to tutoring students who leave the school halfway through colleges. Master Thesis, Institute of Defense Information, National Defense University, Taipei.
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Zhao Ruilin 2007. Research on Reducing Student Attrition with Data Mining Technology. Master Thesis. Institute of Information Management, Yunlin University of Science and Technology, Taiwan
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Department of Statistics, Taiwan Ministry of Education 2014. Overview of the suspension of college and university students in the 2014 academic year. Retrieved from http://stats.moe.gov.tw/files/chart/103
Index Terms
- University Dropout Prevention through the Application of Big Data
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Published In
August 2020
120 pages
ISBN:9781450375467
DOI:10.1145/3416028
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- Southwest Jiaotong University
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Association for Computing Machinery
New York, NY, United States
Publication History
Published: 21 September 2020
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- Research-article
- Research
- Refereed limited
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IMMS 2020
IMMS 2020: 2020 3rd International Conference on Information Management and Management Science
August 7 - 9, 2020
London, United Kingdom
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