移动学习环境中基于案例的上下文感知内容排序方法模型

H. Supic
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引用次数: 4

摘要

学习者移动环境的不断变化产生了多种学习语境。本文描述了移动学习环境中基于案例的上下文感知内容排序方法模型。由于学习资源的教育特征、学习情境和学习者特征之间的依赖关系过于复杂,设计具有自适应内容排序的移动学习教学系统需要付出巨大的努力。根据所提出的方法,提出了一个基于上下文感知的基于案例的内容排序的移动有限自动机辅导(MoFAT)系统原型。外交部的学习资料组织有四个层次的层次结构。一个新的内容排序问题(一个新的案例)是通过找到一个相似的过去案例,并在新的内容排序问题上下文中重用它来解决的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A model of a case-based approach to context-aware content sequencing in Mobile learning environments
The continually changing learner's mobile environment gives rise to many learning context. This paper describes a model of a case-based approach to context-aware content sequencing in mobile learning environments. The design of mobile learning teaching systems with adaptive content sequencing requires significant effort, since dependencies between educational characteristics of learning resources, learning context and learner characteristics are too complex. According to the proposed approach, an prototype of Mobile Finite Automata Tutoring (MoFAT) system using a context-aware case-based content sequencing is presented. The MoFAT's learning material organization has a hierarchical structure with four levels. A new content sequencing problem (a new case) is solved by finding a similar past case, and reusing it in the new content sequencing problem context.
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