滞后序列分析法在学习行为分析中的应用

The Application of Lag Sequential Analysis Method in Analyzing Learning Behavior

学习分析技术的出现为实现高阶的个性化在线学习提供了新的解决思路。学习行为分析是学习分析的重要组成部分,通过对学习过程中记录下来的相关行为数据进行有目的的分析,挖掘出隐藏在行为数据背后的有价值信息。该文从分析方法的角度切入探讨学习行为分析,重点介绍滞后序列分析法(LSA)在学习行为分析中的具体应用思路和策略。LSA可以帮助研究者和教学者准确把握学习者潜在的行为模式,从行为视角阐释技术增强学习效果的原因,同时有效指导后续教与学活动的设计与实施。LSA既可以分析外显操作行为也可以分析内隐交互行为。实际应用中主要有三种策略,分别是分析整个活动过程的行为模式、分析不同阶段行为模式以及分析高低成就组行为模式。

Learning analytics provides a new way to improve the quality of online learning and achieve higher levels of personalized learning. Learning behavior analysis is an important part of learning analytics. It aims to find out valuable information hiding behind the behavior data recorded in the learning process. This study aims to explore the applications and strategies of lag sequential analysis（LSA） in the learning behavior analysis. LSA can help researchers and instructors understand the learner＇s potential behavior patterns more accurately, and explain why technology can enhance learning effect from the perspective of behavior. The result of LSA can effectively guide the design and implementation of the following teaching and learning activities. LSA can not only analyze the explicit operational behaviors but also the implicit interaction behavior. In practice, there are mainly three strategies, including analyzing behavioral patterns in the whole activity, analyzing behavioral patterns in different phases, and analyzing behavioral patterns between the high- and low-achievement groups.