基于智能分析学习行为数据的辅助教学系统设计

On Design of an Auxiliary Teaching System Based on Intelligent Analysis of Learning Behavior Data

当前国开学习网的建设给国开教学提供了巨大的发展机会,也是一个巨大的挑战。开放大学系统的学生在国开网学习、互动研讨、完成作业,这个过程中积累了海量的学生行为数据。有数据有场景是国开推动AI参与教学及考核的良好基础,在AI的视角下来使用这个大规模的复杂数据,通过分析学生学习行为数据来推断学生学习需求,给学生提供基础内容之外不同程度的个性化学习内容和考核指标,建立一套对现有教学考核模式进行有益补充的智能系统,打造一个依赖于学生个体信息及学习行为的学习内容推送模式,进而形成国开教学及考评体系的特色。

At present, the construction of the National Open Learning Network provides a huge opportunity for the development of the National Open Teaching, and it is also a huge challenge. The construction of National Open Learning Network has achieved initial results. A large number of students study and discuss online and finish their homework. In this process, a large number of students’ behavior data have been accumulated. How to make better use of these data to design and build a learning content push mode depending on students’ individual information and learning behavior becomes a feature of the national teaching and evaluation system. Data and scenes are good basis for AI to participate in teaching and assessment. This paper attempts to use this large-scale complex data from the perspective of AI. By analyzing the data of students’ learning behavior, we can infer students’ learning needs, and provide students with different levels of personalized learning content besides the basic content, and set up the assessment index. The establishment of a set of intelligent system can supplement the existing teaching and assessment model.