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

机译:基于关联规则挖掘的学生程序设计成绩影响因素研究

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摘要

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.
机译:计算机编程是每位毕业生必须掌握的最基本技能之一。但是,据报道,他们无法很好地编写程序。研究表明,有许多因素会影响学生的编程表现。因此,本研究的目的是使用数据挖掘技术,根据以前的学生表现信息,研究可能影响学生编程表现的重要因素。数据挖掘是一种数据分析技术,能够发现数据库中的隐藏知识。本研究中使用的编程数据集包含有关11月课程年度信息技术学士学位,多媒体学士学位,决策科学学士学位和教育学学士学位等4个不同学士学位课程的马来西亚Utara大学学生的绩效概况信息2004/2005。根据毕业的要求,他们必须参加入门编程学科。对包含4个19条记录和70个属性的数据集进行预处理,然后使用定向关联规则挖掘算法Apriori进行挖掘。结果表明,在进入大学之前就已经学习过编程的学生,并且在马来西亚中学证书考试中在数学和英语学科上的得分都很高,这些都是有助于提高编程成绩的有力指标。这一发现可以为教师规划新注册学生的教学计划提供指导。

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