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 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 Information 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 pre-processed 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

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 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