摘要
为了提高计算机辅助教学(CAI:Computer Assisted Instruct)课件的质量和教学效果,通过传统的普通CAI课件与基于网络化的CAI课件的对比,分析了网络化的计算机辅助教学的优势和存在的问题。针对存在的问题,基于数据挖掘理论提出了层次生成算法,并将该算法应用于CAI课件系统中,构建课件树,合理组织课件,为学生提供个性化的课件服务。针对该算法中对学生的忽略,利用Hamming距离、按照学生对不同种类的课件使用的频率等信息对学生进行分组,较大地改善了个性化课件系统的效率。
To improve the quality and effect of CAI （Computer Assisted Instruct） courseware system, compared with the traditional CAI courseware system, the network-based CAI courseware system has its advantages and disadvantages. A hierarchical level-generate algorithm is proposed, based on the data mining theory, to cope with its disadvantages by building a CAI courseware tree and organizing the whole eourseware objects into a reasonable structure. By doing this, the system can provide the student with personalized service. But this algorithm overlooked the students. Thus, mining on students were considered. Using Hamming distance theory, students were clustered into different groups based on the courseware they accessed. The performance is greatly improved.
出处
《吉林大学学报（信息科学版）》
CAS
2009年第2期195-200,共6页
Journal of Jilin University（Information Science Edition）
基金
高教部新世纪高等教育教学改革工程基金资助项目(高教研2000B71)
