面向个性化学习的慕课资源推荐系统开发  

Development of MOOC resources recommendation system for personalized learning

作　　者：孔令圆 彭琰 郑汀华 马华 Kong Lingyuan;Peng Yan;Zheng Tinghua;Ma Hua(College of Information Science and Engineering,Hunan Normal University,Changsha,Hunan 410081,China)

机构地区：[1]湖南师范大学信息科学与工程学院,湖南长沙410081

出　　处：《计算机时代》2021年第7期46-49,共4页Computer Era

基　　金：湖南师范大学智能计算与感知类大学生创新创业训练项目(No.1);湖南省普通高等学校教学改革研究项目(湘教通〔2019〕291号,No.140)。

摘　　要：近年来,在线学习得到了大规模普及,互联网上已发布了海量的慕课学习资源。针对广大学习者进行在线慕课学习时面临的“信息迷航”和“信息过载”等问题,以混合推荐算法为基础,通过多角度挖掘用户的个性化信息,设计并实现了一个面向个性化学习的慕课资源推荐系统,以此为广大学习者提供自主学习的辅助支持。该系统能充分挖掘学习者的显式和隐式偏好,为其推荐满意的慕课资源,具有良好的应用价值。In recent years,online learning has been popularized on a large scale,and massive MOOC learning resources have been released on the Internet.Aiming at the problems of"information disorientation"and"information overload"faced by the majority of learners in online MOOC learning,on the basis of hybrid recommendation algorithm,by mining user's personalized information from multiple perspectives,a MOOC resource recommendation system for personalized learning is designed and implemented,in order to provide the majority of learners with the auxiliary support of autonomous learning.The system can fully tap learners'explicit and implicit preferences,and recommend satisfactory MOOC resources for them,which have a good application value.

关 键 词：慕课 学习资源 混合推荐 个性化学习 

分 类 号：G642[文化科学—高等教育学]