慕课教学中基于局部社区发现的主题交互模型  

Topic interaction model based on local community detection for MOOC teaching process

作　　者：石博[1] 何楚[1] 卓桐 徐新[1] 

机构地区：[1]武汉大学电子信息学院,武汉430072

出　　处：《计算机应用研究》2015年第6期1724-1727,共4页Application Research of Computers

基　　金：国家自然科学基金资助项目(41371342;61331016);湖北省自然科学基金资助项目;湖北省教学改革项目(2011008)

摘　　要：针对慕课教学过程中存在的学生能力差异、缺乏针对性等问题,提出一种基于局部社区发现的主题交互模型,对学生能力评估过程进行主题建模,采用局部社区发现算法对学生各方面能力进行合理的等级分类;同时在原有课程实验平台基础上,改进并搭建能够全方位追踪和收集学生行为信息且具有较强交互性的慕课平台。两者结合应用于信号处理系列课程教学实践中,结果表明,主题交互模型对能力评估的准确率明显高于传统考核方式,并且辅以针对性的课堂交流与培养,学生各方面能力均得到不同程度的提高。Aiming at the problems of uneven students＇ abilities and the absence of specificity in M00C teaching process, this paper presented a novel topic interaction model based on the local community detection. It modeled the evaluation process of students＇ ability as hierarchical structure of a topic model. It introduced the local community detection algorithm to reasonably classify various abilities. Meanwhile, based on the original course experiment platform proposed before, it established an im- proved MOOC platform to widely trace the behavior information and provided with highly interaction. Experimental results on the teaching practice of digital signal processing course show that topic interaction model achieves higher accuracy rates com- pared with traditional assessment methods. Supplemented with specific communication and guidance, students＇ abilities can be enhanced effectively to some degree.

关 键 词：慕课 隐含狄利克雷分布 社区发现 主题模型 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]