计算机类课程过程监控型学习行为分析

传统学习行为分析注重事后分析，即根据学习结果评价学习效果。计算机类课程不同于其它领域课程，实践性很强，对学生动手能力要求较高。由于学生在该课程中的学习行为涉及大量动手操作，如建模、编程、测试等，通过监控、存储与分析相关数据，可对学生学习过程持续进行学习行为分析，从而及时发现学生学习中的困难，并给予相应反馈。设计并实现一个BJUTModeling系统平台，以持续监控与记录学生的建模操作数据，并利用频繁序列挖掘技术进行学习分析，取得了较好的实际教学效果。

Analysis of Learning Behaviors in the Courses of Computer Sciences Based on Learning Process Monitoring

Traditional learning behavior analysis focuses on ex-post analysis， which is to evaluate learning effectiveness based on learning outcomes. Computer courses are different from those in other fields， and they are highly practical and have high requirements for students’ hands-on ability. Therefore， student learning behavior involves a lot of hands-on operations such as modeling， programming， testing， and so on. This study proposes to monitor， store and analyze these data to achieve continuous learning behavior analysis in the learning process， so as to find out the difficulties of student learning in time and provide corresponding feedback. Specifically， this study designs and implements the BJUTModeling system， continuously monitors and records students’modeling operation and uses frequent sequence pattern mining， which achieves a good result of teaching.