【摘要】 近几年随着科技和现代教育的发展,数据库和网络技术得到飞速的发展和广泛的应用,智能教学系统也就大量地出现,这样就有大量的数据伴随着出现,而怎样处理这些数据使人们从中获得有用的信息变成一个热门的话题。数据挖掘技术就是将大量数据以一定的方式进行处理,得到对人们有用的信息,来帮助人们学习和预测。将数据挖掘技术引入到教学过程中学生的个人学习素质评估当中,创新性地通过决策树算法和聚类算法相结合的方法对学生数据分析,挖掘潜在的信息资源,找出影响个人综合素质的关键因素及各因素之间的关系,总结优秀学生的个人综合素质的培养方法,弥补不足,提高学生的个人综合素质。更多还原

【Abstract】 In recent years, with the development of science and technology and modern education, database and network technology has been rapid developed and wide applied, so there are amount of data along with the emergence of lots of intelligent tutoring systems appearring, and how to deal with these data so that people can get unexpected information come into a hot topic. Data mining is processing large amount of data in a certain way to give useful information to people and help them to learn and forecast. Transferring data mining technology to assessment of the quality of students’ individual learning during the teaching process creatively combined analytic hierarchy process with decision tree to analyze data of students, and tapping the potential of information resources to identify the key factors that impact individ-ual overall quality and the relationship between various factors and summarize the outstanding cultivate way of the overall quality of out-standing students, making up the shortage and improving students’ overall quality.更多还原