基于大数据分析的计算机网络课程自适应学习系统构建

Construction of an adaptive learning system of computer network course based on big data analysis

大数据时代数字化的学习资源将呈现爆炸式的增长,面对海量的学习资源,学习者如何选择,或者如何向学习者推送合适的学习资源将成为未来面临的主要问题。针对计算机网络课程授课内容多、知识更新快的问题,通过收集教育过程中的学习行为数据,利用大数据的学习分析技术构建了一个计算机网络自适应学习系统,该系统包含自适应、预测、干预等六大模块,可以针对性地推送学习内容,及时反馈学习者的学习效果,并推荐下一步的学习策略,从而达到因材施教和培养学生自主学习能力的效果。

In big data era, digital learning resources are growing explosively. Facing on massive learning resources, how to choose or how to push proper resources to learners will become a major challenge in the future. To overcome the problems of excessive fast update network course contents, we build a computer network adaptive learning system through collecting learning behavior data in the teaching process based on big data analysis. This system contains six modules： adaptive learning, fore-casting, interpose and others, which can push targeted learning contents and feedback learners＇ per-formance in time, thus teaching learners in accordance to their aptitudes.