摘要
文章对在线教师在教学、培训过程中所产生的大量教师数据进行收集和挖掘,其中包括学科特点和学习习惯特点等内容。利用优化的协同过滤算法,精准、高效地推荐个性化在线自我提升学习材料和学习资源,从而提升教师的在线学习效率,帮助教师更有效地完成在线自我提升任务,提升学习的效果。
The article collects and mines a large amount of teacher data generated by online teachers during the teaching and training process,including subject characteristics and learning habits.By utilizing optimized collaborative filtering algorithms,personalized online self improvement learning materials and resources can be accurately and efficiently recommended,thereby improving teachers'online learning efficiency,helping them more effectively complete online self improvement tasks,and enhancing learning effectiveness.
作者
林凌
LIN Ling(Fujian Institute of Education,Fuzhou Fujian 350001,China)
出处
《信息与电脑》
2023年第16期79-82,共4页
Information & Computer
基金
2020年福建省教育厅中青年教师教育科研(科技类)项目(项目编号:JAT201524)。
关键词
教师研修数据
资源推送
算法
teacher training data
resource push
algorithm
