Mining the student programming performance using rough set

Md Norwawi, Norita and Hibadullah, C.F. and Abd Wahab, Mohd Helmy and Mohamad Mohsin, Mohd Farhan (2010) Mining the student programming performance using rough set. In: 2010 International Conference on Intelligent Systems and Knowledge Engineering (ISKE), 15-16 November 2010, Hangzhou.

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Abstract

One of the powerful data mining analysis is it can generates different set of knowledge when similar problem is presented to different data mining techniques. In this paper, a programming dataset was mined using rough set in order to investigate the significant factors that may influence students programming performance based on information from previous student performance. Then, the result was compared with other researches which had previously explored the data using statistic, clustering, and association rule. The dataset consists of 419 records with 70 attributes were pre-processed and then mined using rough set. The result indicates rough set has identified several new characteristics. The student who has been exposed to programming prior to entering university and obtained average score in Mathematics, English, and Malay Language subject during secondary Malaysian School Certificate (SPM) examination were among strong indicators that contributes to good programming grades. Besides that, the personality factor; the investigative and social type plus average cognitive person were also found as important factors that influence programming. This finding can be a guideline for the faculty to plan teaching and learning program for new registered student.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:programming; influence factor; rough set
Subjects:Q Science > QA Mathematics > QA76 Computer software
Divisions:Faculty of Electrical and Electronic Engineering > Department of Computer Engineering
ID Code:3060
Deposited By:Normajihan Abd. Rahman
Deposited On:22 Feb 2013 11:56
Last Modified:21 Jan 2015 15:24

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