• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议> >A distance learning framework for automatic instructor replies: articulable tacit knowledge used for feedback upon request
【24h】

A distance learning framework for automatic instructor replies: articulable tacit knowledge used for feedback upon request

机译：用于自动讲师答复的远程学习框架：根据要求用于反馈的可表达的默认知识

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

Distance learning has many facets, ranging from technology implementations to assessment methods. The last decade has seen an increased number of tools to facilitate virtual classrooms and collaboration. However, feedback and evaluation are only partially automated in online courses. This paper largely follows knowledge management theories and artificial intelligent techniques, developing a framework to capture and manage automated responses to student replies. The instructor's tacit knowledge plays a direct role in augmenting class participation, learning communities, and feedback evaluation. Conceptual graphs are proposed to extract tacit knowledge from instructors written responses and to assist in externalizing it for future re-use. A question answering task is presented to illustrate the relationship between mental models and conceptual graphs and the mechanism to select responses through keyword match.
机译：远程学习涉及很多方面，从技术实施到评估方法。在过去的十年中，出现了越来越多的工具来促进虚拟教室和协作。但是，在线课程中反馈和评估只是部分自动化。本文主要遵循知识管理理论和人工智能技术，开发了一个框架来捕获和管理对学生答复的自动答复。老师的默会知识在增加班级参与度，学习社区和反馈评估方面起着直接作用。提出概念图以从教师的书面答复中提取默会知识，并协助将其隐化以供将来重用。提出了一个问答任务，以说明心理模型与概念图之间的关系以及通过关键字匹配选择响应的机制。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号