个性化协同过滤推荐算法在教师网络研修资源中的应用

Application of personalized collaborative filtering recommendation algorithm in teacher network training resources

现今中小学教育信息化发展迅速,对教师应用信息化教学的能力要求越来越高。为加强中小学学校的信息化建设,提升教师能力,各类网络研修平台应运而生。网络研修的模式在教师学习中广泛应用,成为新时代教师培养良好学习习惯的有效途径。与此同时,社会中各类的教育资源平台与数据库越来越多,教师在研修资源平台上能够搜索到的学习资源越来越多,各平台资源库中资源种类与数量日益增加,从而导致教师查找精确化的资源较为困难,教师研修资源利用率不高。因此通过对个性化协同过滤算法研究,结合学科特点、学科分类、学习模式,对资源进行个性化、精确化推荐,并进行推荐去重,缩短查找资源的时间,使教师可以灵活搜寻和利用资源,增强教师研修的积极性与主动性,提高中小学教师的研修效率。

Nowadays, the informationization of primary and secondary education is developing rapidly, and the ability of teachers to apply informatization teaching is becoming more and more demanding. In order to strengthen the information construction of primary and secondary schools and enhance the ability of teachers, various network training platforms have emerged. The mode of network training is widely used in teacher learning, and it has become an effective way for teachers in the new era to cultivate good study habits. At the same time, more and more educational resource platforms and databases appeared in the society. More and more learning resources can be used by teachers on the training resource platform, and the types and quantities of resources in each platform resource library are increasing, resulting in the difficulties for teachers to find accurate resources, and the resource using rate of teacher training is lower. Therefore, through the research of personalized collaborative filtering algorithm, combined with subject characteristics, subject classification, and learning mode, the resources are personalized and refined, and recommendations are de-emphasized, shortening the time for searching resources, teachers are able to search and utilize resources flexibly, which enhance the enthusiasm and initiative of teacher training and improve the efficiency of training for primary and secondary school teachers.