Increasing Adoption of Smart Learning Content for Computer Science Education
Increasing Adoption of Smart Learning Content for Computer Science Education
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计算机科学教育越来越多地采用智能学习内容
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
M. Wollowski
中科院分区：
文献类型：
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作者：
Peter Brusilovsky;S. Edwards;Amruth N. Kumar;L. Malmi;Luciana Benotti;D. Buck;Petri Ihantola;R. Prince;Teemu Sirkiä;Sergey Sosnovsky;J. Urquiza;Arto Vihavainen;M. Wollowski
计算机科学教育工作者越来越多地使用交互式学习内容来丰富和提高他们的课程教学法。专门为计算机科学教育设计的大量此类学习内容，例如用于学习编程的可视化，模拟和基于Web的环境，现在可用于各种课程。我们称之为智能学习内容。然而，这种学习内容很少在其主网站之外使用，尽管它可以为各地的学习者提供好处。在本文中，我们调查的因素，阻碍传播这些内容在更广泛的计算机科学教育界。为了实现这一目标，我们调查了教育工作者，现有的工具和最近的研究文献，以确定当前的艺术状态，并分析了大量的智能学习内容的例子沿着规范维度的特点。在我们的分析中，我们专注于研究必须解决的技术问题，以支持在计算机科学课程中查找，集成和定制智能学习内容。最后，我们提出了一个新的架构，托管，集成和传播智能学习内容，并讨论了如何可以实现基于现有的协议和标准。
Computer science educators are increasingly using interactive learning content to enrich and enhance the pedagogy of their courses. A plethora of such learning content, specifically designed for computer science education, such as visualization, simulation, and web-based environments for learning programming, are now available for various courses. We call such content smart learning content. However, such learning content is seldom used outside its host site despite the benefits it could offer to learners everywhere. In this paper, we investigate the factors that impede dissemination of such content among the wider computer science education community. To accomplish this we surveyed educators, existing tools and recent research literature to identify the current state of the art and analyzed the characteristics of a large number of smart learning content examples along canonical dimensions. In our analysis we focused on examining the technical issues that must be resolved to support finding, integrating and customizing smart learning content in computer science courses. Finally, we propose a new architecture for hosting, integrating and disseminating smart learning content and discuss how it could be implemented based on existing protocols and standards.