A literature review on learning analytics

S. Lei, Ya Ru Wang, Hong Wang, Dinghui Sun, Y. Cao, Zhong Zheng
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引用次数: 1

Abstract

Learning analytics (LA), through the collection and analysis of the relevant data of students to assess, predict and optimise teaching and learning, provides a reliable technical support for the implementation of individualised teaching. The purpose of this article is to review currently published research studies focusing on learning analytics. This review focuses on the theoretical and practical studies of LA. We summarise the hitherto accumulated state of knowledge concerning LA: (a) theoretical frameworks and models of LA; (b) practical research including the data collection dimension of LA, tools and methods for data mining and analysis, and the relationship between the learners' data and outcomes and (c) the current application status of LA. The conclusion overall suggests that LA has potential to realise individualised teaching and learning. However, it also encounters some challenges.
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学习分析的文献综述
学习分析(LA)通过收集和分析学生的相关数据来评估、预测和优化教与学,为实施个性化教学提供可靠的技术支持。本文的目的是回顾当前发表的关于学习分析的研究。本文从理论和实践两方面综述了LA的研究。我们总结了迄今为止积累的关于LA的知识状况:(a) LA的理论框架和模型;(b)实践研究,包括LA的数据收集维度、数据挖掘和分析的工具和方法、学习者的数据与结果之间的关系;(c) LA的应用现状。总的来说,结论表明洛杉矶有潜力实现个性化的教学和学习。然而,它也遇到了一些挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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