MATHVISION PROTOTYPE USING PREDICTIVE ANALYTICS
Yuzi Mahmud1*, Muhd Syahir Abdul Razak2, Shuzlina Abdul-Rahman3, Mastura Hanafiah4, Amien Ashraf Suhaimi5
1*,3College of Computing Informatics and Media, Universiti Teknologi MARA, Selangor, Malaysia.
2Bitify Dynamics Sdn. Bhd., Petaling Jaya, Selangor, Malaysia.
4Accenture Sdn. Bhd., Tun Razak Exchange, Kuala Lumpur, Malaysia.
5Maxis Broadband Sdn. Bhd., Menara Maxis Kuala Lumpur City Centre Off, Kuala Lumpur, Malaysia.
1*This email address is being protected from spambots. You need JavaScript enabled to view it., 2This email address is being protected from spambots. You need JavaScript enabled to view it., 3This email address is being protected from spambots. You need JavaScript enabled to view it., 4This email address is being protected from spambots. You need JavaScript enabled to view it., 5This email address is being protected from spambots. You need JavaScript enabled to view it.
ABSTRACT
Malaysia is currently going towards Industrial Revolution (IR) 4.0 which makes Science, Technology, Engineering and Mathematics (STEM) subjects become more crucial. IR 4.0 covers a lot of aspects especially in digital transformation in manufacturing, and this certainly requires strong mathematical knowledge. To achieve this goal, students need to have a good foundation in Mathematics subject. However, due to the increased number of students nowadays, teachers are facing challenges to track students’ progress efficiently. In this study, a predictive model has been developed that aims to assist Mathematics teachers in monitoring their students. The prototype, called MathVision, can track students’ progress effectively in each topic and subtopic of Mathematics subject and predict the grades that students will obtain based on the history result. A total of 207 instances was collected among Form 5 students from a government school to represent the samples for the modelling task. The Multiclass Decision Forest algorithm appeared to be the best predictive model with 95.16% accuracy, as compared to Boosted Decision Tree, Logistic Regression, and Neural Network. Flutter framework and Firebase services were used for front-end and back-end system respectively, and Microsoft Power BI was used for data visualization. The result of prototype testing showed that MathVision could predict students’ grade for Quiz 2 based on Quiz 1 performance. MathVision is also capable for real-time prediction that guarantees an immediate response time which can help Mathematics teachers to support students who need further assistance in this subject based on the prediction given. For MathVision’s future improvement, the number of instances needs to increase, and more significant variables need to be added.
Keywords: Data Analytics, IR 4.0, Mathematics, Predictive Model, Real-Time Prediction
Published On: 10 October 2023
