Smart School Multimodal Dataset and Challenges
Smart School Multimodal Dataset and Challenges
复制标题
智能学校多模式数据集和挑战
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
M. Laanpere
中科院分区：
文献类型：
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作者：
L. Prieto;M. Rodríguez;M. Kusmin;M. Laanpere
作为旨在探索爱沙尼亚“智能学校”概念（尤其是 STEM 教育）的研究项目的一部分，我们正在开发的教室和学校不仅可以收集数字痕迹的数据，还可以收集物理痕迹（通过各种传感器）的数据。本研讨会的贡献简要描述了设置以及我们在建立能够生成此类多模式数据集的教室方面的初步努力。本文还描述了我们在设置项目并尝试建立此类数据集时面临的一些最重要的挑战，重点关注在日常、真实的学校环境中进行此操作的具体细节。我们相信，这些挑战为多模式学习分析 (MMLA) 社区在从新兴研究和实践社区转变为主流研究和实践社区时必须面对的挑战提供了一个很好的样本。
As part of a research project aiming to explore the notion of ‘smart school’ (especially for STEM education) in Estonia, we are developing classrooms and schools that incorporate data gathering not only from digital traces, but also physical ones (through a variety of sensors). This workshop contribution describes briefly the setting and our initial efforts in setting up a classroom that is able to generate such a multimodal dataset. The paper also describes some of the most important challenges that we are facing as we setup the project and attempt to build up such dataset, focusing on the specifics of doing it in an everyday, authentic school setting. We believe these challenges provide a nice sample of those that the multimodal learning analytics (MMLA) community will have to face as it transitions from an emergent to a mainstream community of research and practice.