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A Study of Prediction Models for Students Enrolled in Programming Subjects

机译:程序设计专业学生的预测模型研究

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Educational Data Mining (EDM) is very appealing research area which can mine valuable information from educational databases. The mined information from educational data can be used to give assistance to educational decision makers to plan strategies according for different academic courses. The main objective of this paper is to provide an overview of existing models for predicting performance of students who are taking programming course. This paper also focuses on the important attributes of students taking programming courses used by some of the existing studies. Furthermore, the paper also highlights the different classification prediction algorithms to predict the performance of students taking programming courses. The study tries to provide some highlight for new researchers in building a prediction model for programming students. This paper is the step towards improving the quality of education and could bring assistance and impacts to all the educational stakeholders.
机译:教育数据挖掘(EDM)是一个非常吸引人的研究领域,可以从教育数据库中挖掘有价值的信息。从教育数据中提取的信息可用于帮助教育决策者根据不同的学术课程规划策略。本文的主要目的是概述现有模型,以预测正在学习编程课程的学生的表现。本文还重点介绍了参加某些现有研究使用的编程课程的学生的重要属性。此外,本文还重点介绍了用于预测参加编程课程的学生表现的不同分类预测算法。该研究试图为新的研究人员在为学生编程时建立预测模型提供一些亮点。本文是提高教育质量的一步,可以为所有教育利益相关者带来帮助和影响。

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