为学习影响实现学习分析:使用工具完成任务

IF 6.4 1区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Internet and Higher Education Pub Date : 2020-04-01 DOI:10.1016/j.iheduc.2020.100729
Simon Knight , Andrew Gibson , Antonette Shibani
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引用次数: 33

摘要

学习分析有可能大规模地影响学生的学习。这种说法中包含了一系列关于规模本质的假设和紧张关系,对学生学习的影响,以及“学习分析”作为社会技术领域所包含的基础设施范围。根据我们开发学习分析的设计经验,并引导其他人使用它,我们提出了一个模型,我们已经使用它来解决我们遇到的五个关键挑战。在开发这个模型的过程中,我们建议:通过扩大现有的实践来关注对学习的影响;实施学习分析对学习影响的任务中心性;学习在评价学习分析中的相应中心性在跨站点实施学习分析时纳入协同设计方法;对社会和技术基础设施的关注。
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Implementing learning analytics for learning impact: Taking tools to task

Learning analytics has the potential to impact student learning, at scale. Embedded in that claim are a set of assumptions and tensions around the nature of scale, impact on student learning, and the scope of infrastructure encompassed by ‘learning analytics’ as a socio-technical field. Drawing on our design experience of developing learning analytics and inducting others into its use, we present a model that we have used to address five key challenges we have encountered. In developing this model, we recommend: A focus on impact on learning through augmentation of existing practice; the centrality of tasks in implementing learning analytics for impact on learning; the commensurate centrality of learning in evaluating learning analytics; inclusion of co-design approaches in implementing learning analytics across sites; and an attention to both social and technical infrastructure.

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来源期刊
Internet and Higher Education
Internet and Higher Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
19.30
自引率
4.70%
发文量
30
审稿时长
40 days
期刊介绍: The Internet and Higher Education is a quarterly peer-reviewed journal focused on contemporary issues and future trends in online learning, teaching, and administration within post-secondary education. It welcomes contributions from diverse academic disciplines worldwide and provides a platform for theory papers, research studies, critical essays, editorials, reviews, case studies, and social commentary.
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