摘要
针对远程教育环境中,学习者分散、缺乏个性化学习指导等问题,构建了一个基于JADE的学习网络与个性化学习系统。系统为每个学习者创建一个JADE代理,用以动态监控学习行为并实现感兴趣资源的共享、推荐和评估,同时基于其他学习者代理对不同资源的感兴趣程度,通过发现相似性、更新信任权值和调整潜在邻居等方法,动态调整学习者之间的信任关系,构建学习网络,为远程学习者提供更准确地学习资源推荐。实验结果表明系统可以非常迅速的将具有相同兴趣的学习者聚合在一起,并很好的满足他们的查询、推荐需求。
Aiming at the disadvantages in the e - learning environment such as scattered learners, lack of person- alized guidance, etc. , a JADE - based learning community and personalized learning system is constructed. It creates JADE agents for each learner, in order to dynamically monitor the learning behaviors and promote sharing, recommendation and evaluation of the learning resources. Based on the different preferences, the algorithm presented here creates an automatically adapted trust relationship through similarity discovery, trust weights update, potential neighbors adjustment and so on. Experiments show that the system can rapidly gather the learners with similar interests and satisfy their demands of queries and recommendations.
出处
《计算机仿真》
CSCD
2007年第7期301-304,共4页
Computer Simulation
基金
国家自然科学基金项目(60372078)
关键词
海布学习法则
自组织社区
远程学习
Hebbian learning rules
Self - organizing community
E - learning
