Learning in communities of practice (CoPs) makes up a significant portion of today's knowledge gain. However, only little technological support is tailored specifically toward CoPs and their particular strengths and challenges. Even worse, CoPs often do not possess the resources to host or develop a software ecosystem to support their activities. In this contribution, we describe a decentralized learning infrastructure for community knowledge building. It takes into account the constant change of these communities by providing a lightweight and scalable infrastructure, without the need for central coordination or facilitation. As a real use case, we implement a question-based dialog application for inquiry-based learning and ignorance modeling with our infrastructure. Additionally, we explore the possibility of using social bots to connect the services provided by the decentralized infrastructure to communication tools already present in most communities (e.g., chat platforms). Following a design science approach, we describe a multistep evaluation of both the infrastructure and application, together with the improvements made to the resulting artifacts of each step. Our results indicate the relevance of our approach, which may serve as an example of how decentralized learning infrastructures for learning outside of formal settings can be applied by CoPs for knowledge building.

中文翻译：

---

用于社区知识建设的分散式学习基础架构

在实践社区（CoP）中学习占当今知识获取的很大一部分。但是，只有很少的技术支持是专门针对CoP及其特定优势和挑战量身定制的。更糟糕的是，CoP通常没有资源来托管或开发软件生态系统来支持其活动。在此贡献中，我们描述了用于社区知识建设的分散式学习基础架构。它通过提供轻量级和可伸缩的基础结构来考虑这些社区的不断变化，而无需中央协调或协助。作为一个实际用例，我们使用基础结构实现了一个基于问题的对话框应用程序，用于基于查询的学习和无知建模。另外，我们探索了使用社交机器人将分散式基础架构提供的服务与大多数社区中已经存在的通信工具（例如，聊天平台）连接的可能性。遵循设计科学方法，我们描述了基础结构和应用程序的多步骤评估，以及对每个步骤所产生的工件所做的改进。我们的结果表明了我们方法的相关性，这可以作为示例说明CoP如何将分散式学习基础结构用于正式环境之外的学习，以用于知识构建。以及对每个步骤所得结果的改进。我们的结果表明了我们方法的相关性，这可以作为示例说明CoP如何将分散式学习基础结构用于正式环境之外的学习，以用于知识构建。以及对每个步骤所得结果的改进。我们的结果表明了我们方法的相关性，这可以作为一个示例，说明CoP如何将分散式学习基础结构用于正式环境之外的学习，以用于知识构建。