ABSTRACT

Most online learning researchers use resource recommendation and retrieve based on learning performance and learning style to provide accurate learning resources, but it is a closed and passive adaptive way. Learners always do not know the recommendation rationale and just receive the result-oriented recommended resources without having a chance to make a procedural reflection and self-directed adjustment. This study proposed an adaptive learning cognitive map model and developed an online learning system based on this model. The proposed system could represent learners’ knowledge structure and cognitive state that allow learning contents, learning activities, learning paths and learning partners to be adjusted continuously, thus providing learners with appropriate learning resources and initiative reflection opportunities during the whole learning procedure. This study conducted a contrast experiment to evaluate the effectiveness of the proposed system. Students in the experimental group received learning interventions according to their adaptive learning cognitive maps. The result demonstrated that the proposed system with the learning cognitive map improved students’ learning achievement, learning satisfied, user acceptance of information technology and learning interaction while did not reduce or increase cognitive load.

摘要

大多数在线学习研究者采用基于学习表现和学习风格的资源推荐和检索来提供准确的学习资源，但这是一种封闭的、被动的自适应方式。学习者往往不知道推荐的原理，只是接受以结果为导向的推荐资源，而没有机会进行程序性反思和自主调整。本研究提出了自适应学习认知图模型，并基于该模型开发了在线学习系统。所提出的系统可以代表学习者的知识结构和认知状态，允许不断调整学习内容、学习活动、学习路径和学习伙伴，从而在整个学习过程中为学习者提供合适的学习资源和主动反思的机会。本研究进行了对比实验，以评估所提出系统的有效性。实验组的学生根据他们的适应性学习认知图接受学习干预。结果表明，所提出的学习认知图系统提高了学生的学习成绩、学习满意度、用户对信息技术的接受度和学习交互，同时没有减少或增加认知负荷。