基于数字资源推荐的自主学习效果评价研究

Evaluation of Independent Learning Effect Based on Digital Resource Recommendation

随着数字资源的急速增加,学习者从海量信息中筛选出有用信息的时间和成本也随之增大。通过构建基于内容和协同过滤的数字资源推荐模型,提升数字资源向学习者推荐的效率和准确性。对使用者的学习效果从学习动机、自我效能、目标设定和环境因素四个维度,运用层次分析法,分析各指标对自主学习效果的重要程度并对数字资源推荐模型。

With the rapid increase of digital resources,the time and cost for learners to filter out useful information from massive information also increase.By constructing a content-based and collaborative filtering digital resource recommendation model,we can improve the efficiency and accuracy of digital resource recommendation to learners.Then,from the four dimensions of learning motivation,self-efficacy,goal setting and environmental factors,using analytic hierarchy process,this paper analyzes the importance of each index to the effect of autonomous learning,and recommends the model of digital resources.