第七届国际学习分析与知识会议论文集

A. Wise, P. H. Winne, G. Lynch, X. Ochoa, I. Molenaar, S. Dawson, M. Hatala
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引用次数: 11

摘要

LAK'17的主题专门关注学习分析研究的跨学科性质。这个主题扩展了先前会议的工作,这些会议旨在汇集现在包含学习分析的学科领域的多样性。LAK'17提交的论文种类繁多,这表明洛杉矶的研究已经充分利用了真正的跨学科研究模式所带来的好处。虽然这种方法存在固有的复杂性,但LAK'17提出的研究通过应用新颖的方法,尖端的学习技术以及对学习过程的实际影响,为该领域带来了许多兴奋和希望。根据这一主题,会议的目的是提供一个关于学习分析跨学科领域的研究和实践的展示,交流和讨论的论坛。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proceedings of the Seventh International Learning Analytics & Knowledge Conference
The theme for LAK'17 purposely focused on the transdisciplinary nature of research in learning analytics. This theme extends the work of prior conferences that sought to bring together the diversity of disciplinary fields that now comprise learning analytics. The great diversity of papers submitted for LAK'17 demonstrates that LA research has very much embraced the benefits that can be leveraged from a truly transdisciplinary model of research. While there are inherent complexities in such an approach, the research presented for LAK'17 brings much excitement and promise to the field through the application of novel methods, cutting-edge learning technologies, and actual impact on the learning process. Following this theme, the aim of the conference is to provide a forum for presentation, exchange and discussion of research and practices regarding the transdisciplinary field of Learning Analytics.
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