What is it about?
Students' academic performance and progression is the key performance indicator of any educational institution. Students' academic progression may vary due to various factors.
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Why is it important?
Identifying students at risk at an early stage could help to improve the academic progression of students, through academic counselling and close monitoring.
Perspectives
Predictive analytics can discover patterns in data that can lead to meaningful predictions for the unknown data. In the proposed research, students already identified at risk are further categorised into low risk, medium risk and high risk. Student study level, type of assessment, type of module and issues faced by the students are taken as the influencing factors. The research focused on finding the influencing factors with the level of risk through predictive modelling. Research results show the issues faced by the student (academic/personal) as the main influencing factor with type of risk.
Jacintha Menezes
Majan University College
Read the Original
This page is a summary of: Predictive modelling to illustrate factors influencing students at risk, International Journal of Technology Transfer and Commercialisation, January 2020, Inderscience Publishers,
DOI: 10.1504/ijttc.2020.106574.
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