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Unobtrusive Observation of Team Learning Attributes in Digital Learning

机译:在数字学习中毫不夸张地观察团队学习属性

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摘要

This article presents a new framework for unobtrusive observation analytics of knowledge and skills-in-action through continuous collection of data from individuals while they interact with digital assets either as individuals or on problem-solving teams. The framework includes measures of the skill and knowledge areas of collaboration, creativity, personal learning, problem solving, and global sustainability, which are observed during natural production and use of communications, intentional artifacts, and resources in a digital learning space designed for self-directed and team-based learning challenges. The article describes the digital context for data collection and shows some example data and analyses.
机译:本文提出了一个新的框架,用于在个人与个人或解决问题团队与数字资产进行交互时,通过不断从个人收集数据来对知识和行动技能进行不打扰的观察分析。该框架包括协作,创造力,个人学习,问题解决和全球可持续性的技能和知识领域的测评,这些测验是在自然生产和使用交流,有意人工制品和为自学设计的数字学习空间中的资源期间观察到的指导和基于团队的学习挑战。本文介绍了数据收集的数字环境,并显示了一些示例数据和分析。

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