An investigation into influence factor of student programming grade using association rule mining

Computer programming is one of the most essential skills which each graduate has to acquire.However, there are reports that they are unable to write a program well. Researches indicated there are many factors can affect student programming performance.Thus, the aim of this study is to investigate th...

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Main Authors: Mohamad Mohsin, Mohamad Farhan, Abd Wahab, Mohd Helmy, Zaiyadi, Mohd Fairuz, Hibadullah, Cik Fazilah
Format: Article
Language:English
Published: 2010
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Online Access:http://repo.uum.edu.my/14738/1/1.pdf
http://repo.uum.edu.my/14738/
http://doi.org/10.4156/aiss.vol2.issue2.3
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spelling my.uum.repo.147382015-07-06T06:39:09Z http://repo.uum.edu.my/14738/ An investigation into influence factor of student programming grade using association rule mining Mohamad Mohsin, Mohamad Farhan Abd Wahab, Mohd Helmy Zaiyadi, Mohd Fairuz Hibadullah, Cik Fazilah QA75 Electronic computers. Computer science Computer programming is one of the most essential skills which each graduate has to acquire.However, there are reports that they are unable to write a program well. Researches indicated there are many factors can affect student programming performance.Thus, the aim of this study is to investigate the significant factors that may influence students programming performance based information from previous student performance using data mining technique. Data mining is a data analysis technique that able to discover hidden knowledge in database. The programming dataset used in this study comprises information on the performance profile of Universiti Utara Malaysia students from 4 different bachelor programs that were Bachelor in Information Technology , Bachelor in Multimedia, Bachelor in Decision Science and Bachelor in Education specializing in IT of the November session year 2004/2005. They were required to enroll introductory programming subject as requirement to graduate . The dataset consisting of 4 19 records with 70 attributes were pre-processed and then mined using directed association rule mining algorithm namely Apriori. The result indicated that the student who has been exposed to programming prior to entering university and scored well in Mathematics and English subject during secondary Malaysian School Certificate examination were among strong indicators that contributes to good programming grades. This finding can be a guideline to the faculty to plan a teaching and learning program for new registered student. 2010 Article PeerReviewed application/pdf en http://repo.uum.edu.my/14738/1/1.pdf Mohamad Mohsin, Mohamad Farhan and Abd Wahab, Mohd Helmy and Zaiyadi, Mohd Fairuz and Hibadullah, Cik Fazilah (2010) An investigation into influence factor of student programming grade using association rule mining. Advances in Information Sciences and Service Sciences, 2 (2). pp. 19-27. ISSN 1976-3700 http://doi.org/10.4156/aiss.vol2.issue2.3 doi:10.4156/aiss.vol2.issue2.3
institution Universiti Utara Malaysia
building UUM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Utara Malaysia
content_source UUM Institutionali Repository
url_provider http://repo.uum.edu.my/
language English
topic QA75 Electronic computers. Computer science
spellingShingle QA75 Electronic computers. Computer science
Mohamad Mohsin, Mohamad Farhan
Abd Wahab, Mohd Helmy
Zaiyadi, Mohd Fairuz
Hibadullah, Cik Fazilah
An investigation into influence factor of student programming grade using association rule mining
description Computer programming is one of the most essential skills which each graduate has to acquire.However, there are reports that they are unable to write a program well. Researches indicated there are many factors can affect student programming performance.Thus, the aim of this study is to investigate the significant factors that may influence students programming performance based information from previous student performance using data mining technique. Data mining is a data analysis technique that able to discover hidden knowledge in database. The programming dataset used in this study comprises information on the performance profile of Universiti Utara Malaysia students from 4 different bachelor programs that were Bachelor in Information Technology , Bachelor in Multimedia, Bachelor in Decision Science and Bachelor in Education specializing in IT of the November session year 2004/2005. They were required to enroll introductory programming subject as requirement to graduate . The dataset consisting of 4 19 records with 70 attributes were pre-processed and then mined using directed association rule mining algorithm namely Apriori. The result indicated that the student who has been exposed to programming prior to entering university and scored well in Mathematics and English subject during secondary Malaysian School Certificate examination were among strong indicators that contributes to good programming grades. This finding can be a guideline to the faculty to plan a teaching and learning program for new registered student.
format Article
author Mohamad Mohsin, Mohamad Farhan
Abd Wahab, Mohd Helmy
Zaiyadi, Mohd Fairuz
Hibadullah, Cik Fazilah
author_facet Mohamad Mohsin, Mohamad Farhan
Abd Wahab, Mohd Helmy
Zaiyadi, Mohd Fairuz
Hibadullah, Cik Fazilah
author_sort Mohamad Mohsin, Mohamad Farhan
title An investigation into influence factor of student programming grade using association rule mining
title_short An investigation into influence factor of student programming grade using association rule mining
title_full An investigation into influence factor of student programming grade using association rule mining
title_fullStr An investigation into influence factor of student programming grade using association rule mining
title_full_unstemmed An investigation into influence factor of student programming grade using association rule mining
title_sort investigation into influence factor of student programming grade using association rule mining
publishDate 2010
url http://repo.uum.edu.my/14738/1/1.pdf
http://repo.uum.edu.my/14738/
http://doi.org/10.4156/aiss.vol2.issue2.3
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score 13.211869