A bayesian network approach to identify factors affecting learning of Additional Mathematics

Additional Mathematics is an elective subject in Sijil Pelajaran Malaysia (SPM). However, it is treated as a core subject for almost all the science stream students. Many students who can perform well in Modern Mathematics since primary school cannot master the Additional Mathematics. They fail to u...

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Main Authors: Ong, Hong Choon, Kumarenthiran A/L Chandrasekaran
Format: Article
Language:English
Published: penerbit ukm 2015
Online Access:http://journalarticle.ukm.my/9444/
http://journalarticle.ukm.my/9444/
http://journalarticle.ukm.my/9444/1/Chap11new.pdf
id ukm-9444
recordtype eprints
spelling ukm-94442016-12-14T06:49:57Z http://journalarticle.ukm.my/9444/ A bayesian network approach to identify factors affecting learning of Additional Mathematics Ong, Hong Choon Kumarenthiran A/L Chandrasekaran, Additional Mathematics is an elective subject in Sijil Pelajaran Malaysia (SPM). However, it is treated as a core subject for almost all the science stream students. Many students who can perform well in Modern Mathematics since primary school cannot master the Additional Mathematics. They fail to understand the concepts in Additional Mathematics. This study seeks to identify the factors that affect students in mastering Additional Mathematics at five schools in an urban area. Bayesian network is used to identify the relationship between the factors in the study and to analyze the data as it is able to represent the variables as nodes and the relationships as directed arcs. Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. It is concluded that the new symbols and sign learned in Additional Mathematics affects the students in mastering the subject. penerbit ukm 2015 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/9444/1/Chap11new.pdf Ong, Hong Choon and Kumarenthiran A/L Chandrasekaran, (2015) A bayesian network approach to identify factors affecting learning of Additional Mathematics. Jurnal Pendidikan Malaysia, 40 (2). pp. 185-192. ISSN 0126-6020 / 2180-0782 http://www.ukm.my/jurfpend/articles_for_vol_40(2)_2015.html
repository_type Digital Repository
institution_category Local University
institution Universiti Kebangasaan Malaysia
building UKM Institutional Repository
collection Online Access
language English
description Additional Mathematics is an elective subject in Sijil Pelajaran Malaysia (SPM). However, it is treated as a core subject for almost all the science stream students. Many students who can perform well in Modern Mathematics since primary school cannot master the Additional Mathematics. They fail to understand the concepts in Additional Mathematics. This study seeks to identify the factors that affect students in mastering Additional Mathematics at five schools in an urban area. Bayesian network is used to identify the relationship between the factors in the study and to analyze the data as it is able to represent the variables as nodes and the relationships as directed arcs. Constraint-based algorithms and score-based algorithms are used to generate the networks into several categories to compare and identify the strong relationships among the factors that affect the students’ learning of the subject. It is concluded that the new symbols and sign learned in Additional Mathematics affects the students in mastering the subject.
format Article
author Ong, Hong Choon
Kumarenthiran A/L Chandrasekaran,
spellingShingle Ong, Hong Choon
Kumarenthiran A/L Chandrasekaran,
A bayesian network approach to identify factors affecting learning of Additional Mathematics
author_facet Ong, Hong Choon
Kumarenthiran A/L Chandrasekaran,
author_sort Ong, Hong Choon
title A bayesian network approach to identify factors affecting learning of Additional Mathematics
title_short A bayesian network approach to identify factors affecting learning of Additional Mathematics
title_full A bayesian network approach to identify factors affecting learning of Additional Mathematics
title_fullStr A bayesian network approach to identify factors affecting learning of Additional Mathematics
title_full_unstemmed A bayesian network approach to identify factors affecting learning of Additional Mathematics
title_sort bayesian network approach to identify factors affecting learning of additional mathematics
publisher penerbit ukm
publishDate 2015
url http://journalarticle.ukm.my/9444/
http://journalarticle.ukm.my/9444/
http://journalarticle.ukm.my/9444/1/Chap11new.pdf
first_indexed 2023-09-18T19:54:53Z
last_indexed 2023-09-18T19:54:53Z
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