Identification of Student Behavioral Patterns in Higher Education Using K-Means Clustering and Support Vector Machine

Identification of Student Behavioral Patterns in Higher Education Using K-Means Clustering and Support Vector Machine

In many academic fields, predicting student academic success using data mining techniques has long been a major research issue. Monitoring students in higher education institutions (HEIs) and having the ability to predict student performance is important to improve academic quality. The objective of...

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Bibliographic Details
Main Authors: Nur Izzati Mohd Talib, Nazatul Aini Abd Majid, Shahnorbanun Sahran
Format: Article
Language:English
Published: MDPI AG 2023-03-01
Series:Applied Sciences
Subjects:
student academic performance
identification of student behavioral pattern
higher education
machine learning
support vector machine
k-means clustering
Online Access:https://www.mdpi.com/2076-3417/13/5/3267

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https://www.mdpi.com/2076-3417/13/5/3267

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