Mathematics Performance Monitoring System Using Data Analytics

In recent years, technology has advanced so rapidly to the point where core elements such as Artificial Intelligence (AI), Big Data, Data Analytics, and the Internet of Things (IoT) are becoming trends for Industrial Revolution 4.0 (IR 4.0). The core elements for IR 4.0 have been extensively applied to various major sectors such as Transportation, Retail, Communications, and Education to provide better services while being as efficient as possible. Hence, a system is needed to tackle many students, which has been a limiting factor for teachers to track students' progress efficiently. This research highlights the application of data analytics in mathematics due to its importance in IR 4.0. Predictive analytics has been specifically chosen to help educators gain valuable insight into their students' strengths and weaknesses in each subtopic in Mathematics. Several machine learning algorithms have been used, such as Multiclass Decision Forest, Multiclass Decision Tree, Multiclass Logistic Regression and Multiclass Neural Network. The best model was trained with Multiclass Decision Forest with an accuracy of 95.16%. Several future improvements have been mentioned, such as increasing the number of instances, adding more significant variables, and deploying the system into mobile platforms.