Pattern extraction for programming performance evaluation using Directed Apriori
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...
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| Main Authors: | , , , |
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| Format: | Article |
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| Online Access: | http://eprints.uthm.edu.my/2489/ http://eprints.uthm.edu.my/2489/1/pattern_extraction_for_programming_2.pdf |
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| Summary: | 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. |
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