智能教育生态系统

D. Obolensky, V. Shevchenko
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引用次数: 0

摘要

在本文中,作者探讨了用于远程教育的现代方法,定义了远程学习的问题,如反馈问题、相关性问题、寻找必要课程的问题以及课程的重要性,并考虑到以能力为基础的知识获取范式。在研究过程中,作者考察了可以改善反馈和获得的知识质量的想法,使研究对象个性化。作者还建议使用工作和简历数据集来寻找这些改进所需的重要统计数据。个性化教育路径是根据个人技能、学生认知能力和目标而形成的。考虑了覆盖网络形式的知识概念模型。目前的解决方案,可用于建立个人教育轨迹的分析进行了,特别是,一个差异化的
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Intelligent Educational Ecosystems
In this article, the author explores modern approaches used in distance education, defines the problems of distance learning, such as the problem of feedback, relevance, the search for the necessary courses, as well as the importance of courses, taking into account the competency-based paradigm of knowledge acquisition. During the research, the author examines ideas that can improve feedback and the quality of knowledge gained, personalize the subjects studied. The author suggests also to use job and CV datasets to find important statistic data required for these improvements. The idea of individual educational paths is being studied, which are formed depending on individual skills, student cognitive abilities as well as his goals. The conceptual model of knowledge in the form of an overlay network is considered. The analysis of current solutions that can be used to build individual educational trajectories is carried out, in particular, a differentiated
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