Using Azure Machine Learning to Detection of At-Risk Students
DOI:
https://doi.org/10.52731/lir.v003.089Keywords:
Institutional Research (IR), Azure Machine Learning, early alert system, required subjectAbstract
An important issue in higher education is the systematic monitoring of student achievement stability in programs; an Institutional Research (IR) department found that students were falling behind in grades, so IR would provide an academic counseling mechanism. This study uses Azure Machine Learning (AML) cloud to establish an early alert system that enables teachers to provide tutorial support to students struggling with their coursework. The required subject and elective subject determine the student's total semester grade. Students often raise their overall grades by giving loose grades to elective subjects. This study will eliminate the disruptions caused by lenient electives and provide timely support for students who need to be alerted to required subjects.
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