Predictive Analytics for Tertiary Learners in New Zealand Who Are at Risk of Dropping Out of Education

被引:0
|
作者
Xu, Wenying [1 ]
Luo, Scott [1 ]
Hacksley, Stephanie [1 ]
Trewinnard, Tim [1 ]
Cambridge, Stuart [2 ]
Nik, Syen Jien [1 ]
机构
[1] Jade Software Corp, Christchurch, New Zealand
[2] Tertiary Educ Commiss, Wellington, New Zealand
来源
DATA MINING, AUSDM 2019 | 2019年 / 1127卷
关键词
Predictive modelling; Tertiary Education; Learner success;
D O I
10.1007/978-981-15-1699-3_20
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This industry showcase covers a proof-of-concept predictive model in the education sector of New Zealand. Jade Software worked with New Zealand's Tertiary Education Commission on research to find out how to predict the likelihood of learners dropping out. Our model informs the implementation of intervention programs to support learners in completing their qualifications. The goal of this research is to identify a common data set across multiple types of tertiary education organizations and develop predictive models using the data set. We found that the Single Data Return is a viable data source to form a base model. By comparing the area under the receiver operator characteristic curve, we show that additional data sources, including the attendance data and the learner's results, are helpful in improving model performance. We also developed an interactive dashboard to facilitate estimating the return on investment for intervention programs and the optimal intervention threshold.
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页码:249 / 255
页数:7
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