智能社区中的社会行为和学习

Pub Date : 2014-09-20 DOI:10.55612/s-5002-022-001psi
M. Dascalu, Philippe Dessus, Nicolae Nistor, Stefan Trausan-Matu
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引用次数: 2

摘要

智慧社区是社会创新的核心。基于人和知识的网络,这些社区能够促进社会知识建设。此外,这种社会知识建设过程可以通过互动产生更充分和改进的决策过程;专注于工作、学习或政策定义。智能社区的分析和基准测试对于调查每个社区的演变,以及产生社会互动、知识建设和学习的模型至关重要,这些模型同时创建了集体智慧的基础。在此背景下,本期IxD&A期刊的特刊汇集了四项教育技术研究,涵盖了智能社区的不同方面,重点介绍了它们的基础技术。作者对这一现象作了如下讨论。在本期的第一篇文章“设计智能知识建筑社区”中,Ambar Murillo Montes de Oca、Nicolae Nistor(德国慕尼黑大学)、Mihai Dascalu和E ' t tefan Trausan-Matu(罗马尼亚布加勒斯特Politehnica大学)对知识建筑社区(KBC)进行了更广泛的研究。kbc代表了参与者参与协作话语的环境,伴随着概念性工件的开发和使用,而集体知识库正在逐渐扩展。建议为这些社区使用自动工具,以促进和监视协作话语和概念工件的开发和使用。最后,对智能KBCs的设计提出了建议。根据之前对KBC的定义,在“在线知识建设社区中的新人整合”一文中:作者Nicolae Nistor (Ludwig-Maximilians-Universitat Munchen,德国),Costin-Gabriel Chiru(罗马尼亚布加勒斯特Politehnica大学)和Nicolas Bresser (Universitat der Bundeswehr,德国慕尼黑)通过使用自动分析工具来比较两种对话在词汇链出现和动画间时刻方面的情况,寻找现有KBCs中新人融入的预测因素。此外,Zinayida Petrushyna、Ralf Klamma和Matthias Jarke(德国莱茵-威斯特法利斯理工大学亚琛分校)在他们的文章《文化对智能社区技术的影响:13个维基百科实例的案例》中认为,智能社区能够为自己提供监控社区内社会行为的技术。然而,支持知识构建的底层技术应该考虑社区成员的文化背景。由于不同文化背景的用户以不同的方式构建知识,因此可以使用社会网络分析来定义不同文化背景下智能社区中使用的技术的不同需求。采用不同的观点,Thomas Kohler, Sander Munster和Lars Schlenker(德国德累斯顿工业大学)在他们的论文《虚拟现实中的智能社区》中进行了尝试。“学术教育设计方法的比较”,通过采用“虚拟现实”(VR)来定义智能社区,其中潜在的教育场景特别令人感兴趣。总的来说,VR提供了在沟通和协作过程中的社交互动方面创造复杂学习和工作环境的可能性。随后,智慧社区还应该建立VR生态系统,同时为各种利用ICT进行教学的教育社区提供支持。除了广泛采用信息通信技术之外,智能社区还可以从虚拟现实技术的使用中获益,以弥合成员合作中的空间和时间差距。总而言之,自然语言处理技术、话语分析、社交网络分析、虚拟现实和其他分析工具共同勾勒出一个全面的工具包,旨在捕捉智能社区中发生的社交互动和学习过程的多个方面。
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Social Behaviors and Learning in Smart Communities
Smart communities are at the heart of social innovation. Based on networks of people and knowledge, these communities are able to foster social knowledge building. Moreover, this social knowledge building process may produce through interaction more adequate and improved decision-making processes; focusing on work, learning, or policy definition. Smart communities’ analysis and benchmarking is of paramount importance for investigating the evolution of each community, and for producing models of social interaction, knowledge building and learning that concurrently create the basis of collective intelligence.Against this background, this special issue of the IxD&A journal brings together four educational technology studies covering different facets of smart communities, with an emphasis on their underlying technologies. The authors discuss the phenomenon as follows. In first article in this issue, “Designing Smart Knowledge Building Communities”, Ambar Murillo Montes de Oca, Nicolae Nistor (Ludwig-Maximilians-Universitat Munchen, Germany), Mihai Dascalu and E˜tefan Trausan-Matu (University Politehnica of Bucharest, Romania) take a larger perspective on knowledge building communities (KBC). KBCs represent environments where participants are engaged in collaborative discourse, along with the development and the use of conceptual artifacts, while the collective knowledge base is gradually being expanded upon. Automatic tools are suggested for such communities in order to foster and monitor the development and use of collaborative discourse and conceptual artifacts. Finally, recommendations for the design of smart KBCs are provided. In keeping with the previous definition of KBC, in the article “Newcomer Integration in Online Knowledge Building Communities: Automated Dialogue Analysis in Integrative vs. Non-Integrative Blogger Communities” the authors Nicolae Nistor (Ludwig-Maximilians-Universitat Munchen, Germany), Costin-Gabriel Chiru (University Politehnica of Bucharest, Romania) and Nicolas Bresser (Universitat der Bundeswehr, Munchen, Germany) search for predictors of newcomer integration in existing KBCs by employing an automated analysis tool for comparing two dialogues in terms of lexical chain occurrences and inter-animation moments. Further on, Zinayida Petrushyna, Ralf Klamma and Matthias Jarke (Rheinisch-Westfalische Technische Hochschule Aachen, Germany) in their article “The Impact of Culture On Smart Community Technology: The Case of 13 Wikipedia Instances” perceive smart communities as being capable of providing themselves with technologies for monitoring social behaviors inside communities. Nevertheless, the underlying technologies that support knowledge building should consider the cultural background of community members. Since users with different cultural backgrounds build knowledge in different ways, social network analysis can be employed to define the different requirements for the technologies used in smart communities across different cultures. Taking a different perspective, Thomas Kohler, Sander Munster and Lars Schlenker (Technische Universitat Dresden, Germany), attempt in their paper “Smart communities in virtual reality. A comparison of design approaches for academic education” to define smart communities by adopting „virtual reality” (VR) for a wide variety of purposes, among which potential educational scenarios are of particular interest. Overall, VR offers the possibility to create complex learning and working environments in terms of social interaction in communication and collaboration processes. Subsequently, smart communities should also establish a VR ecosystem while providing support for a variety of educational communities that make use of ICT for teaching and learning. Beyond the widespread adoption of ICT, smart communities can especially profit from the use of VR technologies in order to bridge spatial and time gaps in members’ collaborations. All in all, natural language processing techniques, discourse analysis, social networks analysis, virtual reality and other analytics tools concur to outline a comprehensive toolkit aimed at capturing the multiple facets of social interaction and of learning processes that take place in smart communities.
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