Abstract:

Machine learning is gaining increasing popularity in the education sector due to its potential to improve various aspects of the education system. The present study develops and compares eight types of predictive models with four different machine-learning algorithms to predict students’ academic performance.

The first four predictive models were developed based on the:
(i) demographical,
(ii) academic background,
(iii) parents support, and
(iv) learning behaviour features; and the other four predictive models were generated based on the:
(i) demographical,
(ii) academic background,
(iii) parents support features.

The four machine learning algorithms used in the study include the decision tree, the naïve Bayes, the support vector machine and the neural network. From the result analysis of the dataset, it shows that support vector machine classifier performs high prediction on students’ academic performance.

The findings also reveal that learning behaviour feature is significant and have a greater impact on students’ academic performance.

Keywords:

Learning Analytics, Machine Learning, Predictive Model, Learning Management System.