Current state and future trends: a citation network analysis of the learning analytics field

S. Dawson, D. Gašević, George Siemens, Srécko Joksimovíc
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引用次数: 328

Abstract

This paper provides an evaluation of the current state of the field of learning analytics through analysis of articles and citations occurring in the LAK conferences and identified special issue journals. The emerging field of learning analytics is at the intersection of numerous academic disciplines, and therefore draws on a diversity of methodologies, theories and underpinning scientific assumptions. Through citation analysis and structured mapping we aimed to identify the emergence of trends and disciplinary hierarchies that are influencing the development of the field to date. The results suggest that there is some fragmentation in the major disciplines (computer science and education) regarding conference and journal representation. The analyses also indicate that the commonly cited papers are of a more conceptual nature than empirical research reflecting the need for authors to define the learning analytics space. An evaluation of the current state of learning analytics provides numerous benefits for the development of the field, such as a guide for under-represented areas of research and to identify the disciplines that may require more strategic and targeted support and funding opportunities.
现状与未来趋势:学习分析领域的引文网络分析
本文通过分析LAK会议和已确定的特刊期刊上的文章和引文,对学习分析领域的现状进行了评估。学习分析这一新兴领域是众多学科的交叉点,因此借鉴了多种方法、理论和基础科学假设。通过引文分析和结构化映射,我们旨在确定影响该领域发展的趋势和学科层次的出现。结果表明,主要学科(计算机科学和教育)在会议和期刊代表性方面存在一些碎片化。分析还表明,通常被引用的论文更具有概念性,而不是实证研究,这反映了作者需要定义学习分析空间。对当前学习分析状态的评估为该领域的发展提供了许多好处,例如为代表性不足的研究领域提供指南,并确定可能需要更多战略性和针对性支持和资金机会的学科。
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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