Using predictive modelling to identify students at risk of poor university outcomes

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• 作者：Pengfei Jia ; Tim Maloney
• 关键词：Educational finance and efficiency ; Resource allocation ; Predictive risk modelling ; University dropout behavior ; New Zealand ; I21 ; I22 ; I28
• 刊名：Higher Education
• 出版年：2015
• 出版时间：July 2015
• 年：2015
• 卷：70
• 期：1
• 页码：127-149
• 全文大小：791 KB
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• 作者单位：Pengfei Jia (1)
  Tim Maloney (1)
  
  1. Economics Department, Faculty of Business and Law, Auckland University of Technology, Private Bag 92006, Auckland, 1142, New Zealand
  
• 刊物类别：Humanities, Social Sciences and Law
• 刊物主题：Education
  Education
  
• 出版者：Springer Netherlands
• ISSN：1573-174X

文摘

Predictive modelling is used to identify students at risk of failing their first-year courses and not returning to university in the second year. Our aim is twofold. Firstly, we want to understand the factors that lead to poor first-year experiences at university. Secondly, we want to develop simple, low-cost tools that would allow universities to identify and intervene on vulnerable students when they first arrive on campus. This is why we base our analysis on administrative data routinely collected as part of the enrollment process from a New Zealand university. We assess the ‘target effectiveness-of our model from a number of perspectives. This approach is found to be substantially more predictive than a previously developed risk tool at this university. For example, observations from validation samples in the top decile of risk scores account for nearly 28?% of first-year course non-completions and 22?% of second-year student non-retentions at this university.