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Study of the Dataflow Problem in Complex Adaptive Collaboration Learning Scripts

机译:复杂自适应协作学习脚本中的数据流问题研究

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The flow of artifacts or dataflow in learning design has not been adequately tackled by the IMS-LD specification or other existing Educational Modelin Languages. Several proposed approaches, including the LeadFlow4LD, aim to handle the main dimensions of the dataflow problem, i.e. automation, consistency and reuse. However, considering the adaptive and complex nature of real collaborative learning scripts may have a significant impact in the existing solutions to the dataflow problem. This paper presents an analysis of the potential/limitation of LeadFlow4LD in a real case study, in which a script based on CLFPs and that requires adaptation has been used. Findings of such an analysis suggest the use of workflow templates in order to overcome the detected problems of real reusable designs.
机译:IMS-LD规范或其他现有的教育模型语言尚未充分解决学习设计中的工件流或数据流问题。包括LeadFlow4LD在内的几种提议的方法旨在处理数据流问题的主要方面,即自动化,一致性和重用性。但是,考虑到实际协作学习脚本的自适应性和复杂性,可能会对数据流问题的现有解决方案产生重大影响。本文介绍了在实际案例研究中对LeadFlow4LD的潜力/局限性的分析,其中使用了基于CLFP且需要自适应的脚本。进行此类分析的结果建议使用工作流模板,以克服实际可重用设计中检测到的问题。

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