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基于微世界自适应学习的“微世界图”智能创作
Intelligent Authoring of ’Graph of Microworlds’ for Adaptive Learning with Microworlds |
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| 课程网址: |
http://videolectures.net/qr09_horiguchi_iag/
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| 主讲教师: |
Tomoya Horiguchi, Tsukasa Hirashima
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| 开课单位: |
广岛大学
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| 开课时间: |
2009-07-22
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| 课程语种: |
日语
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| 中文简介: |
在科学教育中，重要的是将一系列微观世界（这意味着一个系统及其模型仅限于教育观点）按照各种复杂性顺序排列到学习环境中。我们之前提出了微观世界图（GMW），这是一个基于模型索引一组微世界的框架。通过使用GMW，可以自适应地选择学生接下来要学习的微观世界，并协助他在微观世界之间进行转换。然而，描述GMW并不容易，因为作者必须具备建模过程中的专业知识。在本研究中，我们提出了一种通过引入组合方法来半自动化GMW描述的方法。我们的方法帮助创作者生成一组索引的微观世界，并且还忽略了关系之间关系的教育意义。我们介绍如何设计这样的功能，并说明它是如何工作的。用原型系统进行的初步测试表明了我们的方法的有效性。
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| 课程简介: |
In science education, it is important to sequence a set of microworlds (which means a system and its model limited from educational viewpoint) of various complexity adaptively to the context of learning. We previously proposed Graph of Microworlds (GMW), a framework for indexing a set of microworlds based on their models. By using GMW, it is possible to adaptively select the microworld a student should learn next, and to assist him in transferring between microworlds. However, it isn’t easy to describe GMW because an author must have the expertise in the process of modeling. In this research, we propose a method for semi-automating the description of GMW by introducing the compositional modeling mechanism. Our method assists an author in generating a set of indexed microworlds and also in considering educational meanings of the relations between them. We present how to design such a function and also illustrate how it works. A preliminary test with a prototype system showed the effectiveness of our method.
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| 关 键 词: |
微观世界; 模型索引; 微世界
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| 课程来源: |
视频讲座网
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| 最后编审: |
2019-09-14：lxf
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| 阅读次数: |
93
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