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Use of machine learning techniques for educational proposes: a decision support system for forecasting students' grades

机译:使用机器学习技术进行教育提议:用于预测学生成绩的决策支持系统

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摘要

Use of machine learning techniques for educational proposes (or educational data mining) is an emerging field aimed at developing methods of exploring data from computational educational settings and discovering meaningful patterns. The stored data (virtual courses, e-learning log file, demographic and academic data of students, admissions/registration info, and so on) can be useful for machine learning algorithms. In this article, we cite the most current articles that use machine learning techniques for educational proposes and we present a case study for predicting students' marks. Students' key demographic characteristics and their marks in a small number of written assignments can constitute the training set for a regression method in order to predict the student's performance. Finally, a prototype version of software support tool for tutors has been constructed.
机译:将机器学习技术用于教育建议(或教育数据挖掘)是一个新兴领域,旨在开发从计算教育环境中探索数据并发现有意义的模式的方法。存储的数据(虚拟课程,电子学习日志文件,学生的人口统计和学术数据,录取/注册信息等)对于机器学习算法很有用。在本文中,我们引用了使用机器学习技术进行教育建议的最新文章,并提供了一个预测学生成绩的案例研究。学生的主要人口统计学特征及其在少量书面作业中的成绩可以构成回归方法的训练集,以便预测学生的表现。最后,构建了针对教师的软件支持工具的原型版本。

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