Pattern extraction for programming performance evaluation using Directed Apriori

Mohamad Mohsin, Mohd Farhan and Zaiyadi, Mohd Fairuz and Md Norwawi, Norita and Abd Wahab, Mohd Helmy Pattern extraction for programming performance evaluation using Directed Apriori. Compilation of Papers 2009 - VOLUME 2 .

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Abstract

Computer programming is taught as a core subject in Information Technology related studies. It is one of the most essential skills which each student has to acquire. However, there is still a small number of students who are unable to write a program well. Several researches indicated that there are many factors which can affect student programming performance. Thus, the objective of this paper is to investigate the significant factors that may influence students programming performance using information from previous student performance. Since data mining data analysis able to discover hidden knowledge in database, a programming dataset which comprises information about performance profile of Bachelor of lnformation Technology students of Faculty of IT, Universiti Utara Malaysia in the year 2004-2005 were explored using data mining technique. The dataset consists of 421 records with 70 mixture type of attributes were preprocessed and then mined using directed association rule (AR) mining algorithm namely apriori. The result indicated that the student who has a programming experience in advanced before starts learn programming in university and scored well in Mathematics and English subject during SPM were among the factor that contributes to a good programming grades.

Item Type:Article
Uncontrolled Keywords:association rule; apriori; programming factor
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK6630-6687 Television. Digital video
ID Code:2489
Deposited By:Normajihan Abd. Rahman
Deposited On:07 May 2012 08:40
Last Modified:07 May 2012 08:40

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