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Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]

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 k...

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Main Authors: Mahmud, Yuzi, Abdul Razak, Muhd Syahir, Abdul-Rahman, Shuzlina, Hanafiah, Mastura, Suhaimi, Amien Ashraf
Format: Article
Language:English
Published: Universiti Teknologi MARA Press (Penerbit UiTM) 2023
Subjects:
Prediction analysis
Online Access:https://ir.uitm.edu.my/id/eprint/86382/1/86382.pdf
https://ir.uitm.edu.my/id/eprint/86382/
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spelling my.uitm.ir.863822023-10-31T17:29:15Z https://ir.uitm.edu.my/id/eprint/86382/ Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.] mjoc Mahmud, Yuzi Abdul Razak, Muhd Syahir Abdul-Rahman, Shuzlina Hanafiah, Mastura Suhaimi, Amien Ashraf Prediction analysis 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. Universiti Teknologi MARA Press (Penerbit UiTM) 2023-10 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/86382/1/86382.pdf Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]. (2023) Malaysian Journal of Computing (MJoC) <https://ir.uitm.edu.my/view/publication/Malaysian_Journal_of_Computing_=28MJoC=29/>, 8 (2): 4. pp. 1505-1516. ISSN 2600-8238
institution Universiti Teknologi Mara
building Tun Abdul Razak Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Mara
content_source UiTM Institutional Repository
url_provider http://ir.uitm.edu.my/
language English
topic Prediction analysis
spellingShingle Prediction analysis
Mahmud, Yuzi
Abdul Razak, Muhd Syahir
Abdul-Rahman, Shuzlina
Hanafiah, Mastura
Suhaimi, Amien Ashraf
Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
description 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.
format Article
author Mahmud, Yuzi
Abdul Razak, Muhd Syahir
Abdul-Rahman, Shuzlina
Hanafiah, Mastura
Suhaimi, Amien Ashraf
author_facet Mahmud, Yuzi
Abdul Razak, Muhd Syahir
Abdul-Rahman, Shuzlina
Hanafiah, Mastura
Suhaimi, Amien Ashraf
author_sort Mahmud, Yuzi
title Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
title_short Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
title_full Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
title_fullStr Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
title_full_unstemmed Mathvision prototype using predictive analytics / Yuzi Mahmud ... [et al.]
title_sort mathvision prototype using predictive analytics / yuzi mahmud ... [et al.]
publisher Universiti Teknologi MARA Press (Penerbit UiTM)
publishDate 2023
url https://ir.uitm.edu.my/id/eprint/86382/1/86382.pdf
https://ir.uitm.edu.my/id/eprint/86382/
_version_ 1781709359483453440
score 13.211869

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