KG (Knowledge Generation) and understanding have traditionally been a Human-centric activity. KE (Knowledge Engineering) and KM (Knowledge Management) have tried to augment human knowledge on two separate planes: the first deals with machine interpretation of knowledge while the later explore interactions in human networks for KG and understanding. However, both remain computer-centric. Crowdsourced HC (Human Computations) have recently utilized human cognition and memory to generate diverse knowledge streams on specific tasks, which are mostly easy for humans to solve but remain challenging for machine algorithms. Literature shows little work on KM frameworks for citizen crowds, which gather input from the diverse category of Humans, organize that knowledge concerning tasks and knowledge categories and recreate new knowledge as a computer-centric activity. In this paper, we present an attempt to create a framework by implementing a simple solution, called ExamCheck, to focus on the generation of knowledge, feedback on that knowledge and recording the results of that knowledge in academic settings. Our solution, based on HC, shows that a structured KM framework can address a complex problem in a context that is important for participants themselves.

中文翻译：

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市民人群中的人类计算：知识管理解决方案框架

传统上，KG（知识生成）和理解是以人为中心的活动。KE（知识工程）和KM（知识管理）试图在两个不同的平面上增强人类知识：第一个用于知识的机器解释，而第二个则在人类网络中为KG和理解探索相互作用。但是，两者仍然以计算机为中心。众包的HC（人类计算）最近已利用人类的认知和记忆来生成有关特定任务的各种知识流，这对于人类来说虽然很容易解决，但对机器算法仍然具有挑战性。文献显示，针对公民人群的KM框架几乎没有任何工作，这些框架收集了来自人类不同类别的投入，组织有关任务和知识类别的知识，并以计算机为中心的活动来重新创建新知识。在本文中，我们尝试通过实施一个名为ExamCheck的简单解决方案来创建一个框架，以专注于知识的生成，对该知识的反馈并在学术环境中记录该知识的结果。我们基于HC的解决方案表明，结构化的KM框架可以在对参与者本身很重要的情况下解决复杂的问题。