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Building social-aware software applications for the interactive learning age

机译:构建面向交互式学习时代的社交感知软件应用程序

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There have been a number of frameworks and models developed to support different aspects of interactive learning. Some were developed to deal with course design through the application of authoring tools, whereas others such as conversational, advisory, and ontology-based systems were used in virtual classrooms to improve and support collaborative activities. Although these methodologies have brought new processes and practices to interactive learning systems, current applications have not fully capitalized on the rising power of social computing to discover and explore the wealth of social-based information derived from the communities of practice that are formed. This article presents a comprehensive social computing framework for web-based learning environments that aims at representing a systematic means of acquiring, sharing, and using relationships effectively within an interactive learning environment so that participants can use them to create opportunities to work cooperatively in learning communities with other students. The proposed framework integrates several aspects of those relations into a decision-making criteria engine that is based on social networks and reputation systems. A description of the proposed methodology and its implementation are presented along with an example application. This research is expected to assist participants of online learning classrooms to make decisions that facilitate the exploration and discovery of co-learners while promoting increased awareness of the virtual classroom structure and information exposure given by their social presence.
机译:已经开发了许多框架和模型来支持交互式学习的不同方面。其中一些开发用于通过使用创作工具来处理课程设计,而其他一些例如对话,咨询和基于本体的系统则用于虚拟教室中,以改善和支持协作活动。尽管这些方法为交互式学习系统带来了新的过程和实践,但是当前的应用尚未充分利用社交计算的不断增强的能力来发现和探索从形成的实践社区中获得的大量基于社会的信息。本文为基于Web的学习环境提供了一个全面的社交计算框架,旨在代表一种在交互式学习环境中有效地获取,共享和使用关系的系统方法,以便参与者可以利用它们来创造在学习社区中进行合作工作的机会与其他学生。提议的框架将这些关系的几个方面集成到基于社交网络和声誉系统的决策标准引擎中。与示例应用程序一起,介绍了所建议的方法及其实现。预期这项研究将帮助在线学习教室的参与者做出决策,以促进探索和发现共同学习者,同时提高人们对虚拟教室结构的认识以及他们的社交活动所提供的信息。

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