RED + iC:创建知识模型以支持学科学习结构化数据类型

Yusneyi Y. Carballo Barrera
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引用次数: 0

摘要

本文描述了使用知识工程技术(KE)对与“结构化数据类型”(SDT)主题相关的概念进行建模。主要的动机是帮助在识别这些结构的过程中,这是一个不平凡的过程,这取决于问题的陈述中列出的属性或练习各种各样的静态和动态SDT。使用CommonKADS方法开发资源和先前经验的回顾、建模上下文和知识建模阶段,以创建知识库(KB)。作为表示机制,使用了CML中的语义网络和规范。这项工作的主要成果反映在所获得的知识模型中,并将其整合到一个名为RED +iC的教育工具中,该工具被几组学生使用,他们报告在识别结构化数据类型的过程中受益。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
RED + iC: Creating a Knowledge Model to support subject learning Structured Data Types
This paper describes the use of Knowledge Engineering techniques (KE) for modeling concepts related to the topic "Structured Data Types" (SDT). The main motivation is to help in the process of recognition of these structures, a non-trivial process, which depends on attributes listed in the statement of the problem or exercise for a wide variety of static and dynamic SDT. CommonKADS methodology was used to develop the phases of Review of sources and previous experiences, Modeling Context, and Knowledge Modeling to create a Knowledge Base (KB). As representation mechanisms used a semantic network and specification in CML. The main results of the work are are reflected in the model of knowledge gained and its integration into an educational tool call RED +iC, which was used by several groups of students who reported benefits in the process of recognition of Structured Data Types.
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