分析可以为电子学习系统的可访问性和残疾学生的学习做出哪些贡献?

M. Cooper, Rebecca Ferguson, A. Wolff
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引用次数: 33

摘要

本文探讨了分析在提高电子学习的可访问性和支持残疾学习者学习方面的潜力。在一个大型的五年数据集中,对残疾学生和非残疾学生的完成率进行了比较分析,并对比较留校率的差异进行了分析。学习分析使我们能够识别和理解这些差异,并在未来可以用来集中干预措施,以提高残疾学生的保留率。本文概述了未来研究的议程,重点是关键学习路径。本文旨在激发对学习分析的潜在好处的更广泛的兴趣,因为他们试图确保他们的电子学习的可访问性,并为残疾学生提供支持。
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What can analytics contribute to accessibility in e-learning systems and to disabled students' learning?
This paper explores the potential of analytics for improving accessibility of e-learning and supporting disabled learners in their studies. A comparative analysis of completion rates of disabled and non-disabled students in a large five-year dataset is presented and a wide variation in comparative retention rates is characterized. Learning analytics enable us to identify and understand such discrepancies and, in future, could be used to focus interventions to improve retention of disabled students. An agenda for onward research, focused on Critical Learning Paths, is outlined. This paper is intended to stimulate a wider interest in the potential benefits of learning analytics for institutions as they try to assure the accessibility of their e-learning and provision of support for disabled students.
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