摘要
在学习过程中,由于不同学生个体有不同的学习方式、学习规律、知识基础及兴趣爱好,针对学生在学习过程中各种学习行为产生的数据,构建数据仓库。通过OLAP技术,结合不同行为产生的结果,在线分析学生在不同时间、不同模块产生不同行为的频次分布情况,推测学生的学习状态、学习侧重点、兴趣点、学习效率、学习轨迹与偏科现象等,使教师可以及时作出调整,提供更合理的学习策略,真正做到有科学依据地因材施教。同时,学习平台可以根据推测结果,推荐个性化的学习内容与学习路线,以提高学生学习效率。
In the process of learning, different students have different learning styles, learning rules, knowledge base ests. We build data warehouse about the data of studentsr various kinds of learning behavior in the learning process. the OLAP technology, combined with the results of different behaviors, we can analyze the frequency distribution of studentsr different behaviors in different time and modules on line to speculate students learning state, learning focus, interest point, learning efficiency, learning trajectory, learning branch phenomenon and so on. According to these speculations, teachers can make timely adjustments, provide more reasonable learning strategies, and truly have a scientific basis to teach students in ac cordance with their aptitude. At the same time, learning platforms can recommend personalized learning content and routes to improve the students learning efficiency.
作者
代巧玲
李振
DAI Qiao ling;LI Zhen(College of Information Science and Technology,Normal Education Northeast University,Changchun 130117,China)
出处
《软件导刊》
2018年第10期187-190,共4页
Software Guide
关键词
学习行为
数据仓库
xAPI
个性化推荐
learning behavior
data warehouse
xAPI
personalized recommendation
