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  • 标题:Learning Analytics Pathways to Impact
  • 本地全文:下载
  • 作者:Linda Corrin ; Maren Scheffel ; Dragan Gašević
  • 期刊名称:Australasian Journal of Educational Technology
  • 印刷版ISSN:1449-3098
  • 电子版ISSN:1449-5554
  • 出版年度:2020
  • 卷号:36
  • 期号:6
  • 页码:1-6
  • DOI:10.14742/ajet.6853
  • 语种:English
  • 出版社:Australasian Society for Computers in Learning in Tertiary Education
  • 摘要:The field of learning analytics has evolved over the past decade to provide new ways to view, understand and enhance learning activities and environments in higher education. It brings together research and practice traditions from multiple disciplines to provide an evidence base to inform student support and effective design for learning. This has resulted in a plethora of ideas and research exploring how data can be analysed and utilised to not only inform educators, but also to drive online learning systems that offer personalised learning experiences and/or feedback for students. However, a core challenge that the learning analytics community continues to face is how the impact of these innovations can be demonstrated. Where impact is positive, there is a case for continuing or increasing the use of learning analytics, however, there is also the potential for negative impact which is something that needs to be identified quickly and managed. As more institutions implement strategies to take advantage of learning analytics as part of core business, it is important that impact can be evaluated and addressed to ensure effectiveness and sustainability. In this editorial of the AJET special issue dedicated to the impact of learning analytics in higher education, we consider what impact can mean in the context of learning analytics and what the field needs to do to ensure that there are clear pathways to impact that result in the development of systems, analyses, and interventions that improve the educational environment.
  • 关键词:learning analytics;impact;higher education
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